Portable, open-source solutions for estimating wrist position during reaching in people with stroke

Jeffrey Z Nie,Na-Teng Hung,R James Cotton,Marc W Slutzky,James W Nie

doi:10.1038/s41598-021-01805-2

Abstract

Arm movement kinematics may provide a more sensitive way to assess neurorehabilitation outcomes than existing metrics. However, measuring arm kinematics in people with stroke can be challenging for traditional optical tracking systems due to non-ideal environments, expense, and difficulty performing required calibration. Here, we present two open-source methods, one using inertial measurement units (IMUs) and another using virtual reality (Vive) sensors, for accurate measurements of wrist position with respect to the shoulder during reaching movements in people with stroke. We assessed the accuracy of each method during a 3D reaching task. We also demonstrated each method’s ability to track two metrics derived from kinematics-sweep area and smoothness-in people with chronic stroke. We computed correlation coefficients between the kinematics estimated by each method when appropriate. Compared to a traditional optical tracking system, both methods accurately tracked the wrist during reaching, with mean signed errors of 0.09 ± 1.81 cm and 0.48 ± 1.58 cm for the IMUs and Vive, respectively. Furthermore, both methods’ estimated kinematics were highly correlated with each other (p < 0.01). By using relatively inexpensive wearable sensors, these methods may be useful for developing kinematic metrics to evaluate stroke rehabilitation outcomes in both laboratory and clinical environments.

Highlights

Arm movement kinematics may provide a more sensitive way to assess neurorehabilitation outcomes than existing metrics
Because these compensatory movement are common after stroke, and are encouraged by some forms of physiotherapy, there is growing interest in the use of kinematic assessments as outcome measures, as they can provide objective, high-resolution quantitative measurements that account for compensatory m ovements[8,9,10]
We first investigated the accuracy of the inertial measurement units (IMUs) and Vive (Fig. 1) during reaching by comparing their estimations of endpoint distance (EPD), defined as the distance from the shoulder to the wrist in three dimensions, to those of a Vicon optical tracking system (Fig. 2a,b)

Summary

Introduction

Arm movement kinematics may provide a more sensitive way to assess neurorehabilitation outcomes than existing metrics. For the Vicon, complex static poses (e.g., T-pose, with both arms abducted and elbows straight) and dynamic range-of-motion calibration may be required depending on the skeleton model and desired task[19,20] These movements would be difficult for many people with stroke to achieve, given frequent inability to extend the impaired elbow. Cameras have a long setup time[20], and a large laboratory space free of vision-occluding barriers is required to accommodate the many carefullypositioned cameras These prerequisites make the routine use of these systems to track spatial pose in people with stroke difficult, suboptimal, and infeasible for most hospital settings. IMUs have some disadvantages, such as susceptibility to magnetic field distortion, that can cause substantial error[32]

Methods

Results

Conclusion