Hand Pronation–Supination Movement as a Proxy for Remotely Monitoring Gait and Posture Stability in Parkinson’s Disease

Abstract

The Unified Parkinson’s Disease Rating Scale (UPDRS) is a subjective Parkinson’s Disease (PD) physician scoring/monitoring system. To date, there is no single upper limb wearable/non-contact system that can be used objectively to assess all UPDRS-III motor system subgroups (i.e., tremor (T), rigidity (R), bradykinesia (B), gait and posture (GP), and bulbar anomalies (BA)). We evaluated the use of a non-contact hand motion tracking system for potential extraction of GP information using forearm pronation–supination (P/S) motion parameters (speed, acceleration, and frequency). Twenty-four patients with idiopathic PD participated, and their UPDRS data were recorded bilaterally by physicians. Pearson’s correlation, regression analyses, and Monte Carlo validation was conducted for all combinations of UPDRS subgroups versus motion parameters. In the 262,125 regression models that were trained and tested, the models within 1% of the lowest error showed that the frequency of P/S contributes to approximately one third of all models; while speed and acceleration also contribute significantly to the prediction of GP from the left-hand motion of right handed patients. In short, the P/S better indicated GP when performed with the non-dominant hand. There was also a significant negative correlation (with medium to large effect size, range: 0.3–0.58) between the P/S speed and the single BA score for both forearms and combined UPDRS score for the dominant hand. This study highlights the potential use of wearable or non-contact systems for forearm P/S to remotely monitor and predict the GP information in PD.

Smartwatch-based functional assessment for upper extremity impairment after musculoskeletal injuries: A pilot study

“…The orthogonal coordination system is defined as shown in Figure 1 , with the x- and y- axes representing the planar direction and the z- axis representing the vertical direction. Based on the literature ( Bertomeu-Motos et al, 2018 ; Cakmak et al, 2022 ; Shen, 2016 ) and considering the movement from the calibration position (sitting on a desk and chair with elbow flexed and forearm pronated), the gyro sensor data axes were defined in relation to the anatomical joint movements as follows ( Figure 1 ): (1) yaw — primarily representing the shoulder internal/external rotation angle with partial shoulder adduction/abduction portion, (2) pitch — primarily the elbow flexion/extension and partially including the shoulder flexion/extension, and (3) roll — primarily the forearm supination/pronation axes. An integration matrix, followed by a rotation matrix, was applied to the angular velocity data acquired from the gyro sensor to estimate the roll, pitch, and yaw angles with respect to the initial position and direction.…”