Capturing whole-body mobility of patients with Parkinson disease using inertial motion sensors: Expected challenges and rewards

Abstract

While many studies have reported on the use of kinematic analysis on well-controlled, in-laboratory mobility tasks, few studies have examined the challenges of recording dynamic mobility in home environments. This preliminary study evaluated whole body mobility in eleven patients with Parkinson disease (H&Y 2-4). Patients were recorded in their home environment during scripted and non-scripted mobility tasks while wearing a full-body kinematic recording system using 11 inertial motion sensors (IMU). Data were analyzed with principal component analysis (PCA) in order to identify kinematic variables which best represent mobility tasks. Results indicate that there was a large degree of variability within subjects for each task, across tasks for individual subjects, and between scripted and non-scripted tasks. This study underscores the potential benefit of whole body multi-sensor kinematic recordings in understanding the variability in task performance across patients during daily activity which may have a significant impact on rehabilitation assessment and intervention.

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Learning motor control parameters for motion strategy analysis of Parkinson's disease patients

“…Rahimi et al [1] presented an approach that uses principal component analysis (PCA) to identify kinematic variables that best represent mobility tasks performed by PD patients. This method uses motion data of patients at different stages of PD recorded in their home environments using a full-body motion capture suit.…”

Motion Capture: From Radio Signals to Inertial Signals

“…In particular, in 5-10 years, the gaming scenario will probably be dominated by games where the user will interactively control virtual characters by using some easily wearable devices (at most 4-5 on the whole body, e.g., possible locations could include feet, ankles, wrists, and head [15,17,33]). The medical scenario will instead begin to adopt wearable sensors able to assess health of the patients by remotely measuring vital signs/parameters and allowing patients to freely stay at their homes still keeping a direct connection with their doctors [5,7,18,23,24,25,29,37,38,41,42].…”

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