Identification of postural transitions using a waist-located inertial sensor
Document typeConference report
PublisherSpringer-Verlag Berlin Heidelberg
Rights accessRestricted access - publisher's policy
Analysis of human movement is an important research area, specially for health applications. In order to assess the quality of life of people with mobility problems like Parkinson’s disease (PD) or stroke patients, it is crucial to monitor their daily life activities. The main goal of this work is to characterize basic activities and their transitions using a single sensor located at the waist. This paper presents a novel postural detection algorithm which is able to detect and identify 6 different postural transitions, sit to stand, stand to sit, bending up/down and lying to sit and sit to lying transitions with a sensitivity of 86.5% and specificity of 95%. The algorithm has been tested on 31 healthy volunteers and 8 PD patients who performed a total of 545 and 176 transitions respectively. The proposed algorithm is suitable to be implemented in real-time systems for on-line monitoring applications.
CitationRodriguez, D. [et al.]. Identification of postural transitions using a waist-located inertial sensor. A: International Work-Conference on Artificial Neural Networks. "Advances in computational Intelligence. 12th International Work-Conference on Artificial Neural Networks, IWANN 2013. Puerto de la Cruz, Tenerife, Spain, June 12-14, 2013 Proceedings, Part I-II". Puerto de la Cruz, Tenerife: Springer-Verlag Berlin Heidelberg, 2013, p. 142-149.
- GREC - Grup de Recerca en Enginyeria del Coneixement - Ponències/Comunicacions de congressos 
- AHA - Advanced Hardware Architectures Group - Ponències/Comunicacions de congressos 
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Ponències/Comunicacions de congressos 
- Departament d'Enginyeria Electrònica - Ponències/Comunicacions de congressos 
|IWANN LNCS_7903 ... nrification of 142-149.pdf||326.4Kb||Restricted access|