Abstract：
:Inertial sensing enables field studies of human movement and ambulant assessment of patients. However, the challenge is to obtain a comprehensive analysis from low-quality data and sparse measurements. In this paper, we present a method to estimate gait kinematics and kinetics directly from raw inertial sensor data performing a single dynamic optimization. We formulated an optimal control problem to track accelerometer and gyroscope data with a planar musculoskeletal model. In addition, we minimized muscular effort to ensure a unique solution and to prevent the model from tracking noisy measurements too closely. For evaluation, we recorded data of ten subjects walking and running at six different speeds using seven inertial measurement units (IMUs). Results were compared to a conventional analysis using optical motion capture and a force plate. High correlations were achieved for gait kinematics (ρ⩾0.93) and kinetics (ρ⩾0.90). In contrast to existing IMU processing methods, a dynamically consistent simulation was obtained and we were able to estimate running kinetics. Besides kinematics and kinetics, further metrics such as muscle activations and metabolic cost can be directly obtained from simulated model movements. In summary, the method is insensitive to sensor noise and drift and provides a detailed analysis solely based on inertial sensor data.
journal_name
J Biomechjournal_title
Journal of biomechanicsauthors
Dorschky E,Nitschke M,Seifer AK,van den Bogert AJ,Eskofier BMdoi
10.1016/j.jbiomech.2019.07.022subject
Has Abstractpub_date
2019-10-11 00:00:00pages
109278eissn
0021-9290issn
1873-2380pii
S0021-9290(19)30484-1journal_volume
95pub_type
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