Laboratory of Movement Analysis and Measurement ‐ EPFL

The multidisciplinary research of the Laboratory of Movement Analysis and Measurement aims on improving movement monitoring and analysis in real-world conditions, through the design of wearable systems and algorithms. We are particularly interested to characterise sport performances and pathologies affecting motor function.

News:

February 11, 2020 – Lancet Neurology journal article out Long-term unsupervised mobility assessment in movement disorders.

This Personal View paper (co-authored by Atash Atrsaei PhD student at LMAM) highlights the potential of wearable-based unsupervised monitoring to provide more ecologically and meaningful information to patients than the supervised data acquired in the traditional clinical setting, which in turn can provide researchers with more accurate, granular, and disease-specific measures.

February 7, 2020 – Public presentation of Matteo Mancuso

Matteo Mancuso had his public defense of his thesis: “Evaluation and robotic simulation of the glenohumeral joint”. Th thesis supported by SNSF and LORF was in collaboration with CHUV-DAL.

27th August 2019 – LMAM in Heidi News

Heidi news was dedicated to motion sensor for sport training by introducing the LMAM startup Archinisis based on Fribourg, active in sport technology and present in FORUM 2019.

6th May 2019 – IEEE Journal of Biomedical and Health Informatics article out personalised approach for real-world gait estimation

Abolfazl Soltani at LMAM in collaboration with industry designed a personalised model which took unique gait style of each subject into account to estimate the speed from a wrist sensor. Results demonstrated that the personalized model provided similar performance as GNSS. The study was published online in IEEE Journal of Biomedical and Health Informatics.

Activity

Research

LMAM research focus on the design of wearable and implanted technology to characterize and evaluate pathologies affecting motor function or to study motor performances in sports