Difference between revisions of "Publications:A wearable gait analysis system using inertial sensors Part I : Evaluation of measures of gait symmetry and normality against 3D kinematic data"
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| − | |Name=Sant'Anna, Anita | + | |Name=Sant'Anna, Anita (anisan) (0000-0002-3495-2961) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Laboratoriet för intelligenta system (6703));Wickström, Nicholas (nicholas) (0000-0002-4143-2948) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Laboratoriet för intelligenta system (6703));Zügner, Roland (Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden);Tranberg, Roy (Department of Orthopedics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden) |
|Title=A wearable gait analysis system using inertial sensors Part I : Evaluation of measures of gait symmetry and normality against 3D kinematic data | |Title=A wearable gait analysis system using inertial sensors Part I : Evaluation of measures of gait symmetry and normality against 3D kinematic data | ||
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| Title | A wearable gait analysis system using inertial sensors Part I : Evaluation of measures of gait symmetry and normality against 3D kinematic data |
|---|---|
| Author | |
| Year | 2012 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing |
| Conference | International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012, Vilamoura, Algarve, 1-4 February, 2012 |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:516201 |
| Abstract | Gait analysis (GA) is an important tool in the assessment of several physical and cognitive conditions. The lack of simple and economically viable quantitative GA systems has hindered the routine clinical use of GA in many areas. As a result, patients may be receiving sub-optimal treatment. The present study introduces and evaluates measures of gait symmetry and gait normality calculated from inertial sensor data. These indices support the creation of mobile, cheap and easy to use quantitative GA systems. The proposed method was compared to measures of symmetry and normality derived from 3D kinematic data. Results show that the proposed method is well correlated to the kinematic analysis in both symmetry (r=0.84, p<0.0001) and normality (r=0.81, p<0.0001). In addition, the proposed indices can be used to classify normal from abnormal gait. |
