ISLAB/CAISR - User contributions [en]

Active at Work

2017-10-25T11:09:21Z

Anita.santanna:

Active at Work

2017-10-25T11:09:02Z

Anita.santanna:

Active at Work

2017-10-25T11:08:27Z

Anita.santanna:

Active at Work

2017-10-25T11:07:27Z

Anita.santanna:

File:Active at work summary.jpeg

2017-10-25T11:06:26Z

Anita.santanna:

Active at Work

2017-10-25T11:02:35Z

Anita.santanna:

Active at Work

2017-10-25T11:00:49Z

Anita.santanna:

{{ResearchProjInfo
|Title=Active at Work
|ContactInformation=Anita Sant'Anna
|ShortDescription=Optimizing physical activity at work with personalized decision support among individuals with osteoarthritis
|Description=The aim of Active@Work is to explore if mobile technology including a personalized decision support system, can have any effect on physical activity level, health, work ability, quality of life, work productivity or sick leave among individuals with osteoarthritis (OA). We also aim to study if there is any difference in effect between using mobile technology and activity monitoring alone or when continuous feedback concerning physical activity is added.

Participants will be allocated through a patient education program for OA and randomized into either (A) Patient education program and physical activity monitoring, (B) Intervention A plus continuous feedback concerning physical activity or (C)
Patient education program (control). The intervention will be performed during three months, with measurements at baseline, and follow-ups after 3, 6 and 12 months. Patient-reported outcomes, outcomes from technical devices and register data will be evaluated.

Lund University is responsible for the randomized controlled trial and Halmstad University is responsible for developing the mobile technology and activity support in the project. Inclusion of patients in the project is expected to start in spring 2017 and to continue until 2019. Analyses and manuscript writing will be performed during 2019. This project will show how technological solutions can be used to develop evidence-based treatment models to improve health and work ability which can be effective as first line treatment of OA.
|LogotypeFile=Logo active at work.jpg
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=Final Application 2017-02-20.pdf
|FundingMSEK=369140
|ProjectStart=2017/01/01
|ProjectEnd=2019/12/31
|ApplicationArea=Health Technology
}}
{{ShowResearchProject}}

The aim of Active@Work is to explore if mobile technology including a personalized decision support system, can have any effect on physical activity level, health, work ability, quality of life, work productivity or sick leave among individuals with osteoarthritis (OA). We also aim to study if there is any difference in effect between using mobile technology and activity monitoring alone or when continuous feedback concerning physical activity is added.

Participants will be allocated through a patient education program for OA and randomized into either (A) Patient education program and physical activity monitoring, (B) Intervention A plus continuous feedback concerning physical activity or (C)
Patient education program (control). The intervention will be performed during three months, with measurements at baseline, and follow-ups after 3, 6 and 12 months. Patient-reported outcomes, outcomes from technical devices and register data will be evaluated.

Lund University is responsible for the randomized controlled trial and Halmstad University is responsible for developing the mobile technology and activity support in the project. Inclusion of patients in the project is expected to start in spring 2017 and to continue until 2019. Analyses and manuscript writing will be performed during 2019. This project will show how technological solutions can be used to develop evidence-based treatment models to improve health and work ability which can be effective as first line treatment of OA.

Active at Work

2017-10-25T10:59:53Z

Anita.santanna:

{{ResearchProjInfo
|Title=Active at Work
|ContactInformation=Anita Sant'Anna
|ShortDescription=Optimizing physical activity at work with personalized decision support among individuals with osteoarthritis
|Description=The aim of Active@Work is to explore if mobile technology including a personalized decision support system, can have any effect on physical activity level, health, work ability, quality of life, work productivity or sick leave among individuals with osteoarthritis (OA). We also aim to study if there is any difference in effect between using mobile technology and activity monitoring alone or when continuous feedback concerning physical activity is added.

Participants will be allocated through a patient education program for OA and randomized into either (A) Patient education program and physical activity monitoring, (B) Intervention A plus continuous feedback concerning physical activity or (C)
Patient education program (control). The intervention will be performed during three months, with measurements at baseline, and follow-ups after 3, 6 and 12 months. Patient-reported outcomes, outcomes from technical devices and register data will be evaluated.

Lund University is responsible for the randomized controlled trial and Halmstad University is responsible for developing the mobile technology and activity support in the project. Inclusion of patients in the project is expected to start in spring 2017 and to continue until 2019. Analyses and manuscript writing will be performed during 2019. This project will show how technological solutions can be used to develop evidence-based treatment models to improve health and work ability which can be effective as first line treatment of OA.
|LogotypeFile=Logo active at work.jpg
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=Final Application 2017-02-20.pdf
|FundingMSEK=369140
|ProjectStart=2017/01/01
|ProjectEnd=2019/12/31
|ApplicationArea=Health Technology
}}
The aim of Active@Work is to explore if mobile technology including a personalized decision support system, can have any effect on physical activity level, health, work ability, quality of life, work productivity or sick leave among individuals with osteoarthritis (OA). We also aim to study if there is any difference in effect between using mobile technology and activity monitoring alone or when continuous feedback concerning physical activity is added.

Participants will be allocated through a patient education program for OA and randomized into either (A) Patient education program and physical activity monitoring, (B) Intervention A plus continuous feedback concerning physical activity or (C)
Patient education program (control). The intervention will be performed during three months, with measurements at baseline, and follow-ups after 3, 6 and 12 months. Patient-reported outcomes, outcomes from technical devices and register data will be evaluated.

Lund University is responsible for the randomized controlled trial and Halmstad University is responsible for developing the mobile technology and activity support in the project. Inclusion of patients in the project is expected to start in spring 2017 and to continue until 2019. Analyses and manuscript writing will be performed during 2019. This project will show how technological solutions can be used to develop evidence-based treatment models to improve health and work ability which can be effective as first line treatment of OA.

Active at Work

2017-10-25T10:58:22Z

Anita.santanna:

Active at Work

2017-10-25T10:53:58Z

Anita.santanna:

Active at Work

2017-10-25T10:52:18Z

Anita.santanna: Created page with "{{ResearchProjInfo |Title=Active@Work |ContactInformation=Anita Sant'Anna |ShortDescription=Optimizing physical activity at work with personalized decision support among indiv..."

{{ResearchProjInfo
|Title=Active@Work
|ContactInformation=Anita Sant'Anna
|ShortDescription=Optimizing physical activity at work with personalized decision support among individuals with osteoarthritis
|Description=The aim of this project is to explore if mobile technology including a personalized decision support system, can have any effect on physical activity level, health, work ability, quality of life, work productivity or sick leave among individuals with osteoarthritis.
|LogotypeFile=Logo active at work.jpg
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=Final Application 2017-02-20.pdf
|FundingMSEK=369140
|ProjectStart=2017/01/01
|ProjectEnd=2019/12/31
|ApplicationArea=Health Technology
}}
The aim of Active@Work is to explore if mobile technology including a personalized decision support system, can have any effect on physical activity level, health, work ability, quality of life, work productivity or sick leave among individuals with osteoarthritis (OA). We also aim to study if there is any difference in effect between using mobile technology and activity monitoring alone or when continuous feedback concerning physical activity is added.

Participants will be allocated through a patient education program for OA and randomized into either (A) Patient education program and physical activity monitoring, (B) intervention A plus continuous feedback concerning physical activity or (C) Patient education program (control). The intervention will be performed during three months, with measurements at baseline, and follow-ups after 3, 6 and 12 months. Patient-reported outcomes, outcomes from technical devices and register data will be evaluated.

Lund University is responsible for the randomized controlled trial and Halmstad University is responsible for developing the mobile technology and activity support in the project. Inclusion of patients in the project is expected to start in spring 2017 and to continue until 2019. Analyses and manuscript writing will be performed during 2019. This project will show how technological solutions can be used to develop evidence-based treatment models to improve health and work ability which can be effective as first line treatment of OA.

File:Final Application 2017-02-20.pdf

2017-10-25T10:49:26Z

Anita.santanna:

File:Logo active at work.jpg

2017-10-25T10:48:53Z

Anita.santanna:

Behaviour Recognition for automated cars

2015-10-21T09:27:31Z

Anita.santanna: Created page with "{{StudentProjectTemplate |Summary=Behaviour Recognition for automated cars |Keywords=driver behavior, feature selection, prediction |Prerequisites=Artificial Intelligence, Mac..."

{{StudentProjectTemplate
|Summary=Behaviour Recognition for automated cars
|Keywords=driver behavior, feature selection, prediction
|Prerequisites=Artificial Intelligence, Machine Learning
|Supervisor=Cristofer Englund, Sławomir Nowaczyk, Anita Sant'Anna,
|Examiner=Antanas Verikas
|Author=Cristofer Englund, Sławomir Nowaczyk, Anita Sant'Anna,
}}
== Background ==

There will be a smooth transition towards a fully automated traffic system that will continue for many years. This implies that there will be a mix of automated and manually driven vehicles in traffic. It is therefore important to understand the interactions between automated and manually driven vehicles. By initially studying the human behaviour and transferring that knowledge to automated vehicles we can create behaviours that are interpretable both for humans and for vehicles. This is fundamental knowledge in order to reduce the risk for accidents. The human should be able to understand the behaviour of an automated vehicle at least as good as he/she can interpret the behaviour of a manually driven vehicle.

At hand we have a 3D vision system that can capture and estimate vehicle speed, size, position and from this data motion paths are created and can be used for behaviour analysis. For this project the vision system should be mounted on the road infrastructure and measure vehicle behaviour in a road section where there are no formal rules but where the drivers apply social rules to interact with each other.

The thesis project will focus on the identification of features, or cues, that describe the intention of a driver, for example, in a narrow road section where vehicles can not meet (see figure below), what is the vehicle behaviour that leads to a negotiation of which vehicle passes first?

== Project description ==

The project should include the following tasks
* Literature review
* Data collection and preparation
* Data analysis
* Variable selection and modelling of driver (vehicle) behaviour
* Writing report/paper

[[Image:Car negotiation.png]]

File:Car negotiation.png

2015-10-21T09:27:08Z

Anita.santanna:

Smart App for PD

2015-09-25T13:22:58Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=A smart-watch app for monitoring symptoms in Parkinson's Disease
|Programme=Information Technology; Embedded Intelligent Systems
|Keywords=Android app development, signal processing, inertial sensors, movement analysis
|References=Pérez-López, Carlos, et al. "Monitoring Motor Fluctuations in Parkinson’s Disease Using a Waist-Worn Inertial Sensor." Advances in Computational Intelligence. Springer International Publishing, 2015. 461-474.

LeMoyne, Robert, and Timothy Mastroianni. "Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor." Mobile Health Technologies: Methods and Protocols (2015): 335-358.
|Prerequisites=courses in signal analysis or image analysis, design of embedded intelligent systems, and programming are required. Previous experience with Java or app development and courses in artificial intelligence are appreciated.
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Level=Master
|Status=Open
}}
Research question: How to implement power efficient signal processing methods on a smart-watch for monitoring motor symptoms in Parkinson's Disease? What are the accuracy vs. power efficiency trade-offs to be considered and how to decide appropriately?

The project will review general signal analysis approaches to monitoring motor symptoms using inertial sensors, make an inventory of the requirements and characteristics of each method, select or modify a method that would be appropriate for implementation on a smart-watch, and execute the implementation and testing of the solution.

Deliverables will include and inventory (literature review) of signal processing methods for monitoring motor symptoms in Parkinson's Disease; and a prototype implementation of the solution on a Moto 360 smart-watch.

A scientific publication based on this project work is encouraged.

Smart App for PD

2015-09-25T13:08:49Z

Anita.santanna: Created page with "{{StudentProjectTemplate |Summary=A smart-watch app for monitoring symptoms in Parkinson's Disease |Programme=Information Technology; Embedded Intelligent Systems |Keywords=An..."

{{StudentProjectTemplate
|Summary=A smart-watch app for monitoring symptoms in Parkinson's Disease
|Programme=Information Technology; Embedded Intelligent Systems
|Keywords=Android app development, signal processing, inertial sensors, movement analysis
|References=Pérez-López, Carlos, et al. "Monitoring Motor Fluctuations in Parkinson’s Disease Using a Waist-Worn Inertial Sensor." Advances in Computational Intelligence. Springer International Publishing, 2015. 461-474.

LeMoyne, Robert, and Timothy Mastroianni. "Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor." Mobile Health Technologies: Methods and Protocols (2015): 335-358.
|Prerequisites=courses in signal analysis or image analysis, design of embedded intelligent systems, and programming are required. Previous experience with Java or app development and courses in artificial intelligence are appreciated.
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Level=Flexible
|Status=Open
}}
Research question: How to implement power efficient signal processing methods on a smart-watch for monitoring motor symptoms in Parkinson's Disease? What are the accuracy vs. power efficiency trade-offs to be considered and how to decide appropriately?

The project will review general signal analysis approaches to monitoring motor symptoms using inertial sensors, make an inventory of the requirements and characteristics of each method, select or modify a method that would be appropriate for implementation on a smart-watch, and execute the implementation and testing of the solution.

Deliverables will include and inventory (literature review) of signal processing methods for monitoring motor symptoms in Parkinson's Disease; and a prototype implementation of the solution on a Moto 360 smart-watch.

A scientific publication based on this project work is encouraged.

Activity monitoring for AAL

2015-09-25T12:43:56Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=Tracking of more than one person in a smart environment using fixed sensors and a mobile robot
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=Ambient assisted living, activity monitoring, activity recognition, tracking and localization, sensors, mobile robot
|TimeFrame=2014-02-01 / 2014-05-31
|References=Beth Logan et al. A Long-Term Evaluation of Sensing Modalities for Activity Recognition. Ubiquitous Computing. Lecture Notes in Computer Science vol. 4717, pp. 483-50, 2007.

Juan Carlos Augusto, Hideyuki Nakashima, Hamid Aghajan. Ambient Intelligence and Smart Environments: A State of the Art. Handbook of Ambient Intelligence and Smart Environments, pp 3-31, 2010.
|Prerequisites=Sensor System (7.5 credits), Learning Systems (7.5 credits), Cooperating Intelligent Systems (7.5 credits), or similar
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Author=Jianyuan Ma, Yinan Qiu
|Level=Master
|Status=Finished
}}
Ambient Assisted Living applications have the potential to support healthy and safe aging at home, alleviating the future demands in healthcare. Many works have addressed the monitoring of an individual at home, however when more than one person is present in the environment, the task is not trivial. This project will investigate the use of both environmental (fixed) sensors and a mobile robot in order to track and monitor the activities of two (possibly more) individuals in the same environment. The result of the project should be a framework for solving the problem as well as a demo/experiment validating the proposed framework.

Activity monitoring for AAL

2015-09-25T12:43:46Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=Tracking of more than one person in a smart environment using fixed sensors and a mobile robot
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=Ambient assisted living, activity monitoring, activity recognition, tracking and localization, sensors, mobile robot
|TimeFrame=2014-02-01 / 2014-05-31
|References=Beth Logan et al. A Long-Term Evaluation of Sensing Modalities for Activity Recognition. Ubiquitous Computing. Lecture Notes in Computer Science vol. 4717, pp. 483-50, 2007.

Juan Carlos Augusto, Hideyuki Nakashima, Hamid Aghajan. Ambient Intelligence and Smart Environments: A State of the Art. Handbook of Ambient Intelligence and Smart Environments, pp 3-31, 2010.
|Prerequisites=Sensor System (7.5 credits), Learning Systems (7.5 credits), Cooperating Intelligent Systems (7.5 credits), or similar
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Author=Jianyuan Ma, Yinan Qiu
|Level=Master
|Status=Ongoing
}}
Ambient Assisted Living applications have the potential to support healthy and safe aging at home, alleviating the future demands in healthcare. Many works have addressed the monitoring of an individual at home, however when more than one person is present in the environment, the task is not trivial. This project will investigate the use of both environmental (fixed) sensors and a mobile robot in order to track and monitor the activities of two (possibly more) individuals in the same environment. The result of the project should be a framework for solving the problem as well as a demo/experiment validating the proposed framework.

Robotic First aid response

2015-09-25T12:41:28Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=A robot system which assesses a person's state of health as a first step toward autonomous robotic first aid/ems
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=robot first aid, injury localization, anomalous breathing recognition, bleeding recognition
|TimeFrame=2015/1/16-2015/6/30
|References=(first aid teleoperated robots)
http://www.uasvision.com/2014/10/29/ambulance-drone-with-integrated-defibrillator/
http://www.technologyreview.com/news/411865/a-robomedic-for-the-battlefield/
(fall detection example) Simin Wang, Salim Zabir, Bastian Leibe. Lying Pose Recognition for Elderly Fall Detection
(breathing recognition) Phil Corbishley and Esther Rodriguez-Villegas. 2008. Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 55, NO. 1, JANUARY 2008
|Prerequisites=Image analysis, sensors systems, learning systems, cooperating intelligent systems or similar;
Some ability to work with software (installing libraries and writing code), and interest in robots, healthcare, or recognition
|Supervisor=Martin Cooney, Anita Sant'Anna
|Examiner=Antanas Verikas
|Author=Tianyi Zhang and Yuwei Zhao
|Level=Master
|Status=Finished
}}
Goal: The capability for a robot in a home or facility to be able to recognize a person's health state when an emergency such as a fall has occurred, as a first step toward endowing robots with critical first aid skills.

Motivation:
Robots need to be useful, and one of the most useful things a robot can do is look after people's health and safety.
A quick and meaningful assessment of a person's state during first response to a possible emergency could help save lives and prevent much anguish.

Challenge: the first thing which should be done is to assess a victim's state, but this is very difficult even for humans;
e.g., for a person who has fallen and unresponsive:
1) where did they hurt themselves?
2) are they breathing normally?
3) are they bleeding?

Focus: this project seeks to show that such recognition is possible for an automatic system, as a proof-of-concept; a simplified in-lab scenario is assumed in which a robot is near the victim and good sensor data can be acquired (visual and sound, without occlusions or noise).

Approach: the students will perform three steps
1) obtain kinect data (skeleton and depth) of a human-shaped dummy falling in different ways
create a recognition system (possibly using LIBSVM) to classify if the head has been hurt
2) record sound samples based on videos of "agonal" respiration, tachypnea (fast breathing),
and regular breathing from YouTube
calculate mfcc features with htk
create a recognition system (possibly using LIBSVM) to classify kind of breathing
3) use a robot (possibly Turtlebot) to drag a white glove over a dummy (red ink will symbolize
blood at some areas) to detect the presence/location of deadly bleeding
Evaluation of system: accuracy or similar metric for how often the system detects head trauma, breathing, bleeding

Requirement: some ability to work with software (installing libraries and writing code), and interest in robots, healthcare, or recognition

Deliverable: an intelligent robot system which can assess a victim's state (thesis/report, code, video)

"TROLL": a regenerating robot

2015-09-25T12:40:49Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=A robot which can detect faults on itself and try to mark or fix them
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=regenerative robot, self-detection/body schema, anomaly/fault detection, self-healing/augmentation
|TimeFrame=2015-01-16 - 2015-06-31
|References=(self-detection) K. Gold, B. Scassellati, Using probabilistic reasoning over time to self-recognize, Robotics and Autonomous Systems (2008), doi:10.1016/j.robot.2008.07.006
(body schema) Mai Hikita, Sawa Fuke, Masaki Ogino, Takashi Minato and Minoru Asada. Visual attention by saliency leads cross-modal body representation. IROS - 2008.
(anomaly detection) Takahiro Suzuki, Fumihiro Bessho, Tatsuya Harada and Yasuo Kuniyoshi. Visual Anomaly Detection under Temporal and Spatial Non-uniformity for News Finding Robot. IROS 2011.
(self-augmentation) Luzius Brodbeck and Fumiya Iida. Enhanced Robotic Body Extension with Modular Units, IROS 2012.
|Prerequisites=some capability to work with software, and interest in robots and recognition
|Supervisor=Martin Cooney, Anita Sant'Anna
|Examiner=Antanas Verikas
|Author=Yinrong Ma
|Level=Master
|Status=Finished
}}
Goal: a companion robot which can fix some of its own problems itself

Motivation: people, especially the elderly, cannot be expected to maintain very complex robots; robots should help out

Challenge: it's tough even for humans to repair robots.
For a soft companion robot intended to interact closely with people, two very common problems are:
Degradation of its exterior (marks and scratches)
Motor problems (due to e.g., frayed/loose cables, gears wearing down)

Approach:
To detect the problems above, the student will set up a robot to look at itself periodically
in a mirror while moving, comparing a mental model of itself with what it actually perceives.
Time allowing, the student should also try to develop some capability for the robot to seek to
repair identified problems: marking holes in its exterior and damaged motors, and possibly
robot motions to try to fill holes with foam

Requirement: some capability to work with software, and interest in robots and recognition

Expected results: a thesis/report, code, video

FirstResponse

2015-09-25T12:39:28Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=First response to emergency situation in a smart environment using a mobile robot
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=Image analysis, camera, mobile robot, falls, human-robot interaction, emergency response
|TimeFrame=2014-02-01 / 2014-05-31
|References=Loreto Susperregi, et al. On the Use of a Low-Cost Thermal Sensor to Improve Kinect People Detection in a Mobile Robot. Sensors 2013, 13(11), 14687-14713.

Simin Wang, Salim Zabir, Bastian Leibe. Lying Pose Recognition for Elderly Fall Detection. Proceedings of Robotics: Science and Systems 2011.
|Prerequisites=Image analysis, sensors systems, learning systems, cooperating intelligent systems or similar
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Author=Gloria
|Level=Master
|Status=Finished
}}
Smart homes and ambient assisted living applications can support healthy and safe aging at home. One important safety feature is to be able to detect an emergency situation and take appropriate actions in a timely manner. Mobile robots can complement smart homes with additional mobile sensors such as cameras and Kinect sensors. These robots have the ability to more closely investigate a potential emergency situation such as a fall; initiate interaction with the person who has fallen; and decide on what actions to take given the response or lack of response from the person. This project will investigate different sensor modalities and methods to detect falls and potential emergency situations, as well as human-robot interaction modalities; and emergency response actions to ensure the person’s safety.

Internal/Premises Discussion

2015-02-17T12:53:23Z

Anita.santanna:

Based on the discussion during the lab today, I have created this page to collect ideas about our premises. You are all more than welcome to contribute and express your opinions.

* Should we add an open social area?
** Yes (SN, AS, ...) No (...)
** Should it be at E5 (SN, AS ...) or at F5 (...)
* Do we need at least 2 conference rooms?
** Yes (SN, ...) No (AS, ...)
** Should both be at E5 (...) or one at E5 and one at F5 (SN, AS, ...)
* Do we need a third (smaller) conference/meeting room?
** Yes (SN, ...) No (AS, ...)
* How many people (mostly affects PhD students I guess) should we have in a single office:
** at most 1 (...)
** at most 2 (...)
** at most 3 (SN, AS, ...)
** more than 3 (...)
* How many more office rooms do we need at F5
** less than 3 (...)
** 3-5 (AS, ...)
** 5-10 (...)
** all of them (SN, ...)

Any other ideas?

MoveApp

2014-12-02T14:55:43Z

Anita.santanna:

{{ResearchProjInfo
|Title=MoveApp
|ContactInformation=Anita Sant'Anna
|ShortDescription=A movement analysis application for the Mobile Health Platform
|Description=The MoveApp project aims to develop new tools to support self-management of chronic conditions which are characterized by motor symptoms and loss of motor coordination. The initial application targets Parkinson's Disease patients. The project will be undertaken in two phases, one related to the development of a self-monitoring and visualization tool for patients; and another related to the development of models to support the decision making process for patients and doctors.
|LogotypeFile=Logo MoveApp.jpg
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=DaraLabsProjectPlan2.pdf
|FundingMSEK=2
|ProjectStart=2014/09/01
|ProjectEnd=2016/12/31
|ApplicationArea=Health Technology
}}
{{AssignProjPartner
|projectpartner=Daralabs AB
}}
{{ShowResearchProject}}

With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.

Given the projections for demographic change and the increased demand for health care resources in the future, there is a need to transition our health care system from one where patients passively receive instructions from the doctor, to one where patients are active in managing their own treatment in a partnership with doctors. This new health care paradigm is often referred to as person-centered care or patient-centric care. In order to speed up and facilitate this process we must empower patients with technologies to support self-assessment and self-management.

Self-management is what persons suffering from chronic diseases do to manage their own illness on a daily basis. It is the ability of the patient to deal with symptoms, treatment, and lifestyle changes. One important part of the process is to actively monitor symptoms and manage their impact on quality of life. Unfortunately, for many of these patients there is a lack of continuous and objective assessment of their symptoms and how they change over time. An assessment of the severity of a patient's condition is usually done at the clinic, very few times a year. In between these session, however, the patient can only rely on his or hers subjective feeling of how their symptoms interfere with their normal daily activities.

One problem which arises is that small, progressive changes in symptom severity are usually not felt by the patient. Another problem is that a person's assessment of their own symptoms is very subjective and can be influenced by mood or other psycho-social factors. Not being able to perceive or quantify how symptoms change can also impact patients' motivation to comply with treatment. In some cases, it may even complicate or delay adjusting the patient's medication dosage.

Current mobile monitoring technologies combined with decision support systems can considerably facilitate self-management for patients by: 1) providing objective assessment of symptoms and other health-related information; 2) modeling how symptoms affect and are affected by daily activities and other health factors; and 3) supporting decision by predicting the impact of certain actions or treatment.

File:DaraLabsProjectPlan2.pdf

2014-12-02T14:52:38Z

Anita.santanna:

Activity monitoring for AAL

2014-10-29T15:05:23Z

Anita.santanna:

{{StudentProjectTemplate
|Summary=Tracking of more than one person in a smart environment using fixed sensors and a mobile robot
|Programme=MSc in Embedded and Intelligent Systems, 30 credits
|Keywords=Ambient assisted living, activity monitoring, activity recognition, tracking and localization, sensors, mobile robot
|TimeFrame=2014-02-01 / 2014-05-31
|References=Beth Logan et al. A Long-Term Evaluation of Sensing Modalities for Activity Recognition. Ubiquitous Computing. Lecture Notes in Computer Science vol. 4717, pp. 483-50, 2007.

Juan Carlos Augusto, Hideyuki Nakashima, Hamid Aghajan. Ambient Intelligence and Smart Environments: A State of the Art. Handbook of Ambient Intelligence and Smart Environments, pp 3-31, 2010.
|Prerequisites=Sensor System (7.5 credits), Learning Systems (7.5 credits), Cooperating Intelligent Systems (7.5 credits), or similar
|Supervisor=Anita Sant'Anna,
|Examiner=Antanas Verikas
|Level=Master
|Status=Ongoing
}}
Ambient Assisted Living applications have the potential to support healthy and safe aging at home, alleviating the future demands in healthcare. Many works have addressed the monitoring of an individual at home, however when more than one person is present in the environment, the task is not trivial. This project will investigate the use of both environmental (fixed) sensors and a mobile robot in order to track and monitor the activities of two (possibly more) individuals in the same environment. The result of the project should be a framework for solving the problem as well as a demo/experiment validating the proposed framework.

Anita Sant'Anna

2014-08-26T09:29:19Z

Anita.santanna:

{{Person
|Family Name=Sant'Anna
|Given Name=Anita
|Title=PhD
|Phone=+46 35167849
|Cell Phone=+46735093033
|Position=Assistant Professor
|Email=anita.santanna@hh.se
|Image=photoAnitaNew.jpg
|Office=E526
|url=http://www.linkedin.com/in/anitasantanna
|Subject=Signal Analysis
}}
{{AssignProjects
|project=SELIES
}}
{{AssignProjects
|project=AccelGait
}}
{{AssignProjects
|project=Virtual Smart Grid
}}
{{AssignProjects
|project=Centre for Health Technology Halland - HCH
}}
{{AssignProjects
|project=CAISR Intelligent Environment
}}
{{AssignProjects
|project=EIS-IGS Smart Grids
}}
{{AssignProjects
|project=Science without Borders
}}
{{AssignProjects
|project=MoveApp
}}
{{AssignSubjectAreas
|SubjectArea=Signal Analysis
}}
{{AssignSubjectAreas
|SubjectArea=Learning Systems
}}
{{AssignSubjectAreas
|SubjectArea=Electrical engineering
}}
{{AssignApplicationAreas
|ApplicationArea=Health Technology
}}
{{AssignTeacher
|Teacher=Design of Embedded and Intelligent Systems (15 credits)
}}
{{AssignTeacher
|Teacher=Electrical Circuits (7.5 credits)
}}
{{AssignProjectResponsible
|ResearchProject=AccelGait
}}



{{ShowPerson}}

== '''Current Activities''' ==

* Current Projects
** [http://islab.hh.se/mediawiki/index.php/Health_Technology CAISR Health Technology Application Area]
** [http://islab.hh.se/mediawiki/index.php/CAISR_Intelligent_Environment CAISR Intelligent Environment]
** Understanding inpatient activity levels after orthopedic surgery
** [http://islab.hh.se/mediawiki/index.php/EIS-IGS_Smart_Grids Analyzing energy usage patterns for improving sustainability]

* Research Interests
** Health technology and health innovation
** Human motion analysis
** Data mining and signal analysis for smart grids

* Teaching
** [http://www.hh.se/utbildning/halsoinnovation.65438393.html Health innovation] (Course responsible)
** [http://www.hh.se/english/academics/exchangestudent/coursesforexchangestudents.3010.html?url=752680950%2Fse_proxy%2Futb_kurstillfalle_exchangestudents_en.asp%3FKtAnmKod%3DX3439%26KtTermin%3D20141&sv.url=12.70cf2e49129168da015800067326 Robotic Manipulation ]
** [http://www.hh.se/ide/utbildning/arstudent/kurshemsidor/digitalteknik.5584.html Digital Electronics]
** [http://www.hh.se/sitevision/proxy/english/education/coursesyllabi.3678.html/svid12_70cf2e49129168da015800070213/752680950/se_proxy/utb_kursplan.asp;jsessionid=42994EA1681258ED2A13A7FE143DDA7E?kurskod=DT8007&revisionsnr=1%2C1&format=pdf&lang=SV Design of Embedded and Intelligent Systems ]

{{InsertSubjAreas}}
{{InsertProjects}}
{{PublicationsList}}
[[Category:staff]]

Anita Sant'Anna

2014-08-26T09:28:32Z

Anita.santanna:

{{Person
|Family Name=Sant'Anna
|Given Name=Anita
|Title=PhD
|Phone=+46 35167849
|Cell Phone=+46735093033
|Position=Assistant Professor
|Email=anita.santanna@hh.se
|Image=photoAnitaNew.jpg
|Office=E526
|url=http://www.linkedin.com/in/anitasantanna
|Subject=Signal Analysis
}}
{{AssignProjects
|project=SELIES
}}
{{AssignProjects
|project=AccelGait
}}
{{AssignProjects
|project=Virtual Smart Grid
}}
{{AssignProjects
|project=Centre for Health Technology Halland - HCH
}}
{{AssignProjects
|project=CAISR Intelligent Environment
}}
{{AssignProjects
|project=EIS-IGS Smart Grids
}}
{{AssignProjects
|project=Science without Borders
}}
{{AssignSubjectAreas
|SubjectArea=Signal Analysis
}}
{{AssignSubjectAreas
|SubjectArea=Learning Systems
}}
{{AssignSubjectAreas
|SubjectArea=Electrical engineering
}}
{{AssignApplicationAreas
|ApplicationArea=Health Technology
}}
{{AssignTeacher
|Teacher=Design of Embedded and Intelligent Systems (15 credits)
}}
{{AssignTeacher
|Teacher=Electrical Circuits (7.5 credits)
}}
{{AssignProjectResponsible
|ResearchProject=AccelGait
}}



{{ShowPerson}}

== '''Current Activities''' ==

* Current Projects
** [http://islab.hh.se/mediawiki/index.php/Health_Technology CAISR Health Technology Application Area]
** [http://islab.hh.se/mediawiki/index.php/CAISR_Intelligent_Environment CAISR Intelligent Environment]
** Understanding inpatient activity levels after orthopedic surgery
** [http://islab.hh.se/mediawiki/index.php/EIS-IGS_Smart_Grids Analyzing energy usage patterns for improving sustainability]

* Research Interests
** Health technology and health innovation
** Human motion analysis
** Data mining and signal analysis for smart grids

* Teaching
** [http://www.hh.se/utbildning/halsoinnovation.65438393.html Health innovation] (Course responsible)
** [http://www.hh.se/english/academics/exchangestudent/coursesforexchangestudents.3010.html?url=752680950%2Fse_proxy%2Futb_kurstillfalle_exchangestudents_en.asp%3FKtAnmKod%3DX3439%26KtTermin%3D20141&sv.url=12.70cf2e49129168da015800067326 Robotic Manipulation ]
** [http://www.hh.se/ide/utbildning/arstudent/kurshemsidor/digitalteknik.5584.html Digital Electronics]
** [http://www.hh.se/sitevision/proxy/english/education/coursesyllabi.3678.html/svid12_70cf2e49129168da015800070213/752680950/se_proxy/utb_kursplan.asp;jsessionid=42994EA1681258ED2A13A7FE143DDA7E?kurskod=DT8007&revisionsnr=1%2C1&format=pdf&lang=SV Design of Embedded and Intelligent Systems ]

{{InsertSubjAreas}}
{{InsertProjects}}
{{PublicationsList}}
[[Category:staff]]

MoveApp

2014-05-16T15:54:14Z

Anita.santanna:

{{ResearchProjInfo
|Title=MoveApp
|ContactInformation=Anita Sant'Anna
|ShortDescription=A movement analysis application for the Mobile Health Platform
|Description=With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.

This projects aims at supporting the development of a platform to support mHealth solutions by incrementally developing new tools and applications. We will initially target home rehabilitation applications, where the patient performs exercises without the supervision of a therapist. The goal is to make use of sensors and movement analysis techniques in order to provide relevant feedback to the patient so as to positively affect recovery and health outcomes.
|LogotypeFile=Logo MoveApp.jpg
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=DaraLabsProjectPlan.pdf
|FundingMSEK=2
|ProjectStart=2014/09/01
|ProjectEnd=2016/12/31
|ApplicationArea=Health Technology
}}
{{AssignProjPartner
|projectpartner=Daralabs AB
}}
{{ShowResearchProject}}

File:Logo MoveApp.jpg

2014-05-16T15:54:03Z

Anita.santanna:

MoveApp

2014-05-16T15:47:14Z

Anita.santanna:

{{ResearchProjInfo
|Title=MoveApp
|ContactInformation=Anita Sant'Anna
|ShortDescription=A movement analysis application for the Mobile Health Platform
|Description=With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.

This projects aims at supporting the development of a platform to support mHealth solutions by incrementally developing new tools and applications. We will initially target home rehabilitation applications, where the patient performs exercises without the supervision of a therapist. The goal is to make use of sensors and movement analysis techniques in order to provide relevant feedback to the patient so as to positively affect recovery and health outcomes.
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=DaraLabsProjectPlan.pdf
|FundingMSEK=2
|ProjectStart=2014/09/01
|ProjectEnd=2016/12/31
|ApplicationArea=Health Technology
}}
{{AssignProjPartner
|projectpartner=Daralabs AB
}}
{{ShowResearchProject}}

MoveApp

2014-05-16T15:46:21Z

Anita.santanna:

{{ResearchProjInfo
|Title=MoveApp
|ContactInformation=Anita Sant'Anna
|ShortDescription=A movement analysis application for the Mobile Health Platform
|Description=With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.

This projects aims at supporting the development of a platform to support mHealth solutions by incrementally developing new tools and applications. We will initially target home rehabilitation applications, where the patient performs exercises without the supervision of a therapist. The goal is to make use of sensors and movement analysis techniques in order to provide relevant feedback to the patient so as to positively affect recovery and health outcomes.
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=DaraLabsProjectPlan.pdf
|FundingMSEK=2
|ProjectStart=2014/09/01
|ProjectEnd=2016/12/31
|ApplicationArea=Health Technology
}}
{{AssignProjPartner
|projectpartner=Daralabs AB
}}
{{ShowResearchProject}}

MoveApp

2014-05-16T15:43:49Z

Anita.santanna: Created page with "{{ResearchProjInfo |Title=MoveApp |ContactInformation=Anita Sant'Anna |ShortDescription=A movement analysis application for the Mobile Health Platform |Description=With the gl..."

{{ResearchProjInfo
|Title=MoveApp
|ContactInformation=Anita Sant'Anna
|ShortDescription=A movement analysis application for the Mobile Health Platform
|Description=With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.

This projects aims at supporting the development of a platform to support mHealth solutions by incrementally developing new tools and applications. We will initially target home rehabilitation applications, where the patient performs exercises without the supervision of a therapist. The goal is to make use of sensors and movement analysis techniques in order to provide relevant feedback to the patient so as to positively affect recovery and health outcomes.
|ProjectResponsible=Anita Sant'Anna
|ProjectDetailsPDF=DaraLabsProjectPlan.pdf
|FundingMSEK=2
|ProjectStart=2014/09/01
|ProjectEnd=2016/12/31
|ApplicationArea=Health Technology
}}
{{AssignProjPartner
|projectpartner=Daralabs AB
}}
With the global penetration of smart phones and communication networks, millions of people now use mobile devices as a daily tool for communication, data transfer and much more. As a consequence, possibilities have opened up for new technological advancements to emerge. These technological advancements involve the creation of external hardware solutions that reap the benefits of smart-phones' capabilities in order to become more cost effective and mobile. Devices which enable remote monitoring of patients have been identified as one of the areas most uniquely suited to grow in tandem with this technology. On an international setting, this specific field of technology is often referred to as mHealth and is predicted to grow substantially in the upcoming years.

This projects aims at supporting the development of a platform to support mHealth solutions by incrementally developing new tools and applications. We will initially target home rehabilitation applications, where the patient performs exercises without the supervision of a therapist. The goal is to make use of sensors and movement analysis techniques in order to provide relevant feedback to the patient so as to positively affect recovery and health outcomes.

File:DaraLabsProjectPlan.pdf

2014-05-16T15:38:42Z

Anita.santanna:

Centre for Health Technology Halland - HCH

2014-05-16T15:26:36Z

Anita.santanna:

{{ResearchProjInfo
|Title=Centre for Health Technology Halland - HCH
|ContactInformation=Anne-Christine Hertz
|ShortDescription=Innovation for health.
|Description=The Centre for Health Technology in Halland is a meeting place for businesses, consumers, the municipalities of Halland County, the County Council of Halland and Halmstad University and provides a joint platform for the pursuit of development in the area of health technology. Through co-operative projects and work in innovative environments leading to new products and services, the project seeks to contribute to increasing the pace of innovation and to sharpening the competitive edge of the companies involved.
|LogotypeFile=Hch4a.png
|ProjectResponsible=anne-christine.hertz@hh.se
|FundingMSEK=0
|ProjectStart=2009/08/01
|ProjectEnd=2013/06/30
|ApplicationArea=Health Technology
|Lctitle=No
}}
__NOTOC__

[[File:Hch4a.png|thumb|caption|Centre for Health Technology Halland - HCH]]
[[File:EU_eng_vanster_RGB.jpg|thumb|caption|Financed by "Europeiska regionala utvecklingsfonden"]]

The Centre for Health Technology in Halland is a meeting place for businesses, consumers, the municipalities of Halland County, the County Council of Halland and Halmstad University and provides a joint platform for the pursuit of development in the area of health technology. Through co-operative projects and work in innovative environments leading to new products and services, the project seeks to contribute to increasing the pace of innovation and to sharpening the competitive edge of the companies involved.

http://www.hh.se/6/11.html

Health Technology

2014-05-16T15:19:39Z

Anita.santanna:

{{Infobox
|title = Health Technology
|image = [[Image:Free2measure mätningar 032.JPG|200px]]
|header1 = Research in Health Technology
|header2 = '''Contact:''' [[Anita Sant'Anna]]
|header3 = [[Centre for Health Technology Halland - HCH|Centre for Health Technology Halland (HCH)]]

}}

Our mission is to support healthy and active lifestyles, safe and independent aging, as well as effective care services by developing intelligent systems that are aware of a person’s situation, health, and well-being using affordable, unobtrusive, and ubiquitous sensors. At CAISR, we develop technologies that support the acquisition and analysis of health-related data for monitoring and decision-support. We work with both mobile technologies and intelligent environments, and focus on movement analysis, behavior modeling and deviation detection techniques.

== Projects ==

{{#ask: [[Category:ResearchProject]] [[ApplicationArea::Health Technology]]
| ?ContactInformation
| ?ShortDescription
}}





== People ==
[[File:320Anita_jens.JPG|frame|alt=Anita and Jens|[[Anita Sant'Anna|Anita]] and [[Jens Lundström|Jens]]]]
* [[Anita Sant'Anna]] (Coordinator)
* [[Anne-Christine Hertz]] ([[Centre for Health Technology Halland - HCH|HCH]])
* [[Antanas Verikas]]
* [[Jens Lundström]]
* [[Siddhartha Khandelwal]]
* [[Nicholas Wickström]]
* [[Wagner Ourique de Morais]] ([[CERES]])
* [[Martin Cooney]]
* [[Magnus Hållander]]
* [[Thorsteinn Rögnvaldsson]]

== Industrial Partners ==
* [[Tappa Service AB]]
* [[Neat Electronics AB]]
* [[Swedish Adrenaline]]
* [[Daralabs AB]]

== Academic Partners ==
* [http://www.gpcc.gu.se/english/?languageId=100001&disableRedirect=true&returnUrl=http%3A%2F%2Fwww.gpcc.gu.se%2F University of Gothenburg Centre for Person-centred Care]
* [http://www.orthopaedics.gu.se/Department+of+Orthopaedics/ Department of Orthopaedics at the Sahlgrenska Academy]
* [http://en.ktu.lt/ Kaunas University of Technology]



{{#arraymaptemplate: {{#show: {{PAGENAME}}|?publication|link=none}}
| testPubProjOut
|,
| 
}}

Health Technology

2014-05-16T15:03:29Z

Anita.santanna:

{{Infobox
|title = Health Technology
|image = [[Image:Free2measure mätningar 032.JPG|200px]]
|header1 = Research in Health Technology
|header2 = '''Contact:''' [[Anita Sant'Anna]]
|header3 = [[Centre for Health Technology Halland - HCH|Centre for Health Technology Halland (HCH)]]

}}

== Projects ==

{{#ask: [[Category:ResearchProject]] [[ApplicationArea::Health Technology]]
| ?ContactInformation
| ?ShortDescription
}}





== People ==
* [[Anita Sant'Anna]] (Coordinator)
* [[Anne-Christine Hertz]] ([[Centre for Health Technology Halland - HCH|HCH]])
* [[Antanas Verikas]]
* [[Jens Lundström]]
* [[Siddhartha Khandelwal]]
* [[Nicholas Wickström]]
* [[Wagner Ourique de Morais]] ([[CERES]])
* [[Martin Cooney]]
* [[Magnus Hållander]]
* [[Thorsteinn Rögnvaldsson]]

== Partners ==
* [[Tappa Service AB]]
* [[Neat Electronics AB]]
* [[Swedish Adrenaline]]
* [[Daralabs AB]]

[[File:320Anita_jens.JPG|frame|none|alt=Anita and Jens|[[Anita Sant'Anna|Anita]] and [[Jens Lundström|Jens]]]]

== Publications ==
{{AssignPublicationProject|Publication=Publications:A new measure of movement symmetry in early Parkinson's disease patients using symbolic processing of inertial sensor data}}
{{AssignPublicationProject|Publication=Publications:A Serious Computer Game to Assist Tai Chi Training for the Elderly}}
{{AssignPublicationProject|Publication=Publications:A Symbol-Based Approach to Gait Analysis From Acceleration Signals : Identification and Detection of Gait Events and a New Measure of Gait Symmetry}}
{{AssignPublicationProject|Publication=Publications:A Linguistic Approach to the Analysis of Accelerometer Data for Gait Analysis}}
{{AssignPublicationProject|Publication=Publications:Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems}}
{{AssignPublicationProject|Publication=Publications:A Wearable Accelerometer Based Platform to Encourage Physical Activity for the Elderly}}
{{AssignPublicationProject|Publication=Publications:Gait Unsteadiness Analysis from Motion Primitives}}
{{AssignPublicationProject|Publication=Publications:Exploring similarity-based classification of larynx disorders from human voice}}
{{AssignPublicationProject|Publication=Publications:A feature selection technique for generation of classification committees and its application to categorization of laryngeal images}}
{{AssignPublicationProject|Publication=Publications:A Serial-Parallel Panoramic Filter Bank as a Modelof Frequency Decomposition of Complex Soundsin the Human Inner Ear}}
{{AssignPublicationProject|Publication=Publications:Advances in laryngeal imaging}}
{{AssignPublicationProject|Publication=Publications:Using the patient's questionnaire data to screen laryngeal disorders}}
{{AssignPublicationProject|Publication=Publications:A kernel-based approach to categorizing laryngeal images}}
{{AssignPublicationProject|Publication=Publications:Exploring Kernels in SVM-Based Classification of Larynx Pathology from Human Voice}}

{{#arraymaptemplate: {{#show: {{PAGENAME}}|?publication|link=none}}
| testPubProjOut
|,
| 
}}

Application areas

2014-05-16T14:52:51Z

Anita.santanna:

<div style="width:70%;">
{{Flashybox
|captionbar=Lightblue.jpg
|icon=graph_icon.jpg
|title=[[Intelligent Vehicles]]
|content=Our Intelligent Vehicles research focuses on situation- as well as self- awareness. Situation awareness is relevant for things like autonomous driving, active safety systems, and intelligent material handling. Self-awareness is essential for making operations more efficient, for example regarding fuel consumption, on-board diagnostics, or predictive maintenance.

;'''Contact: ''': [[Roland Philippsen]], Assistant Professor Robotics and Intelligent Vehicles
;'''Contact: ''': [[Björn Åstrand]], Associate Professor Information Technology and Mechatronics
}}

{{Flashybox
|captionbar=Lightblue.jpg
|icon=graph_icon.jpg
|title=[[Health Technology]]
|content=Our mission is to support healthy and active lifestyles, safe and independent aging, as well as effective care services by developing intelligent systems that are aware of a person’s situation, health, and well-being using affordable, unobtrusive, and ubiquitous sensors. At CAISR, we develop technologies that support the acquisition and analysis of health-related data for monitoring and decision-support. We work with both mobile technologies and intelligent environments, and focus on movement analysis, behavior modeling and deviation detection techniques.'' [[Health Technology|more info]]
; '''Contact: ''': [[Anita Sant'Anna]], Assistant Professor Health Technology
; '''Contact: ''': [[Anne-Christine Hertz]], Project Manager, [[Centre for Health Technology Halland - HCH|HCH]]
; '''Companies: ''':{{•|1=''' '''[[Daralabs AB]]}}{{•|1=''' '''[[Neat Electronics AB]]}}{{•|1=''' '''[[Swedish Adrenaline]]}}{{•|1=''' '''[[Tappa Service AB]]|last=1}}
}}

{{Flashybox
|captionbar=Lightblue.jpg
|icon=graph_icon.jpg
|title=[[Biometrics]]
|content=The term “biometrics” refers to automatic recognition of an individual based on behavioral
or anatomical characteristics (e.g., fingerprints, face, iris, voice, signature, etc.). This is done by means of pattern recognition techniques and statistical methods.

;'''Contact: ''': [[Josef Bigun]], Professor Signal Analysis
}}



</div>

Health Technology

2014-05-16T07:56:01Z

Anita.santanna:

{{Infobox
|title = Health Technology
|image = [[Image:Free2measure mätningar 032.JPG|200px]]
|header1 = Research in Health Technology
|header2 = [[Centre for Health Technology Halland - HCH|HCH]]
|header3 = Biomedical engineering
|header4 = '''Contact:''' [[Anita Sant'Anna]]
}}

== Projects ==

{{#ask: [[Category:ResearchProject]] [[ApplicationArea::Health Technology]]

| format=ul
}}

== People ==
* [[Anita Sant'Anna]] (Coordinator)
* [[Anne-Christine Hertz]] ([[Centre for Health Technology Halland - HCH|HCH]])
* [[Antanas Verikas]]
* [[Jens Lundström]]
* [[Siddhartha Khandelwal]]
* [[Nicholas Wickström]]
* [[Wagner Ourique de Morais]] ([[CERES]])
* [[Martin Cooney]]
* [[Magnus Hållander]]
* [[Thorsteinn Rögnvaldsson]]

== Partners ==
* [[Tappa Service AB]]
* [[Neat Electronics AB]]
* [[Swedish Adrenaline]]
* [[Daralabs AB]]

[[File:320Anita_jens.JPG|frame|none|alt=Anita and Jens|[[Anita Sant'Anna|Anita]] and [[Jens Lundström|Jens]]]]

== Publications ==
{{AssignPublicationProject|Publication=Publications:A new measure of movement symmetry in early Parkinson's disease patients using symbolic processing of inertial sensor data}}
{{AssignPublicationProject|Publication=Publications:A Serious Computer Game to Assist Tai Chi Training for the Elderly}}
{{AssignPublicationProject|Publication=Publications:A Symbol-Based Approach to Gait Analysis From Acceleration Signals : Identification and Detection of Gait Events and a New Measure of Gait Symmetry}}
{{AssignPublicationProject|Publication=Publications:A Linguistic Approach to the Analysis of Accelerometer Data for Gait Analysis}}
{{AssignPublicationProject|Publication=Publications:Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems}}
{{AssignPublicationProject|Publication=Publications:A Wearable Accelerometer Based Platform to Encourage Physical Activity for the Elderly}}
{{AssignPublicationProject|Publication=Publications:Gait Unsteadiness Analysis from Motion Primitives}}
{{AssignPublicationProject|Publication=Publications:Exploring similarity-based classification of larynx disorders from human voice}}
{{AssignPublicationProject|Publication=Publications:A feature selection technique for generation of classification committees and its application to categorization of laryngeal images}}
{{AssignPublicationProject|Publication=Publications:A Serial-Parallel Panoramic Filter Bank as a Modelof Frequency Decomposition of Complex Soundsin the Human Inner Ear}}
{{AssignPublicationProject|Publication=Publications:Advances in laryngeal imaging}}
{{AssignPublicationProject|Publication=Publications:Using the patient's questionnaire data to screen laryngeal disorders}}
{{AssignPublicationProject|Publication=Publications:A kernel-based approach to categorizing laryngeal images}}
{{AssignPublicationProject|Publication=Publications:Exploring Kernels in SVM-Based Classification of Larynx Pathology from Human Voice}}

{{#arraymaptemplate: {{#show: {{PAGENAME}}|?publication|link=none}}
| testPubProjOut
|,
| 
}}

Health Technology

2014-05-16T07:53:37Z

Anita.santanna:

{{Infobox
|title = Health Technology
|image = [[Image:Free2measure mätningar 032.JPG|200px]]
|header1 = Research in Health Technology
|header2 = [[Centre for Health Technology Halland - HCH|HCH]]
|header3 = Biomedical engineering
|header4 = '''Contact:''' [[Anita Sant'Anna]]
}}

== Projects ==

{{#ask: [[Category:ResearchProject]] [[ApplicationArea::Health Technology]]

| format=ul
}}

== People ==
* [[Anita Sant'Anna]] (Coordinator)
* [[Anne-Christine Hertz]] ([[Centre for Health Technology Halland - HCH|HCH]])
* [[Antanas Verikas]]
* [[Jens Lundström]]
* [[Siddhartha Khandelwal]]
* [[Magnus Hållander]]
* [[Nicholas Wickström]]
* [[Thorsteinn Rögnvaldsson]]
* [[Wagner Ourique de Morais]] ([[CERES]])

== Partners ==
* [[Tappa Service AB]]
* [[Neat Electronics AB]]
* [[Swedish Adrenaline]]
* [[Daralabs AB]]

[[File:320Anita_jens.JPG|frame|none|alt=Anita and Jens|[[Anita Sant'Anna|Anita]] and [[Jens Lundström|Jens]]]]

== Publications ==
{{AssignPublicationProject|Publication=Publications:A new measure of movement symmetry in early Parkinson's disease patients using symbolic processing of inertial sensor data}}
{{AssignPublicationProject|Publication=Publications:A Serious Computer Game to Assist Tai Chi Training for the Elderly}}
{{AssignPublicationProject|Publication=Publications:A Symbol-Based Approach to Gait Analysis From Acceleration Signals : Identification and Detection of Gait Events and a New Measure of Gait Symmetry}}
{{AssignPublicationProject|Publication=Publications:A Linguistic Approach to the Analysis of Accelerometer Data for Gait Analysis}}
{{AssignPublicationProject|Publication=Publications:Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems}}
{{AssignPublicationProject|Publication=Publications:A Wearable Accelerometer Based Platform to Encourage Physical Activity for the Elderly}}
{{AssignPublicationProject|Publication=Publications:Gait Unsteadiness Analysis from Motion Primitives}}
{{AssignPublicationProject|Publication=Publications:Exploring similarity-based classification of larynx disorders from human voice}}
{{AssignPublicationProject|Publication=Publications:A feature selection technique for generation of classification committees and its application to categorization of laryngeal images}}
{{AssignPublicationProject|Publication=Publications:A Serial-Parallel Panoramic Filter Bank as a Modelof Frequency Decomposition of Complex Soundsin the Human Inner Ear}}
{{AssignPublicationProject|Publication=Publications:Advances in laryngeal imaging}}
{{AssignPublicationProject|Publication=Publications:Using the patient's questionnaire data to screen laryngeal disorders}}
{{AssignPublicationProject|Publication=Publications:A kernel-based approach to categorizing laryngeal images}}
{{AssignPublicationProject|Publication=Publications:Exploring Kernels in SVM-Based Classification of Larynx Pathology from Human Voice}}

{{#arraymaptemplate: {{#show: {{PAGENAME}}|?publication|link=none}}
| testPubProjOut
|,
| 
}}

Daralabs AB

2014-05-16T07:52:30Z

Anita.santanna: Created page with "{{Company |Name=Daralabs AB |Image=Logo Daralabs new.jpg |URL=http://www.daralabs.com/ |Contact=Christian Saleki |Contact Email=christian.saleki@daralabs.com }} The founders o..."

{{Company
|Name=Daralabs AB
|Image=Logo Daralabs new.jpg
|URL=http://www.daralabs.com/
|Contact=Christian Saleki
|Contact Email=christian.saleki@daralabs.com
}}
The founders of DaraLabs got together with a simple vision; To improve the prospects of health care through the means of innovation and creative thinking for people in all parts of the world, regardless of their social status. By combining the availability of smartphones and tablets and our own technologies, DaraLabs’ engineers are able to build cost effective medical devices with the focus on high quality components and beautiful design which offer functionality that can greatly improve the quality of life for many people.

File:Logo Daralabs new.jpg

2014-05-16T07:49:41Z

Anita.santanna:

File:Logo Daralabs.png

2014-05-16T07:45:07Z

Anita.santanna:

Internal

2014-05-16T07:40:10Z

Anita.santanna:

== Information ==
# This is a good start: [[Internal/GettingStarted]]
# Create/edit a page via Form, all in one page [[New Input]]
# [[Wiki Documentation]]
# Project approval procedure for budgets over 500 KSEK [[Internal/ProjectApprovalProcedures]]

Refresh the main page (useful after adding a new "News" item): [http://islab.hh.se/mediawiki/index.php/Main_Page?action=purge http://islab.hh.se/mediawiki/index.php/Main_Page?action=purge]

== Meeting Minutes (Tuesday) ==
<subpages page="Internal/Minutes/islab" sortby="title" format="list" order="desc" />

== TODO ==
[[Internal/Information missing]]

[[Internal/Intelligent Vehicles TODO]]

== Changes to EIS Masters Programme ==
[[Internal/Math Course]]

== Smart Grid Project ==
Meting minutes [http://islab.hh.se/mediawiki/Internal/HEM_Meetings]

== Other pages related to this page ==

<subpages sortby="lastedit" format="list" order="desc" />