Estimation Of Arm Kinematics In Stroke Survivors With Wearable Sensors

Abstract BackgroundStroke is the leading cause of long-term disability in the United States, often resulting in upper extremity (UE) motor impairment. Most existing outcome metrics of UE function in rehabilitation are insensitive to change or subject to observer bias. There is growing interest in using movement kinematics to measure UE motor function, since they can provide high-resolution, quantitative measurements. However, measuring arm kinematics in stroke survivors, particularly in the hospital or clinic, can be challenging for traditional optical tracking systems due to non-ideal environments, expense, and a limited ability to perform required calibration poses. The aim of this study was to develop a general framework for accurate measurements of wrist position during reaching movements in people with stroke using relatively inexpensive wearable sensors.MethodsWe developed and presented two methods, one using inertial measurement units (IMUs) and using virtual reality (Vive) sensors, that practically estimate wrist position with respect to the shoulder. We then assessed the estimation accuracies of each method during a 3D reaching task by using a Vicon motion capture system. We also demonstrated each methods ability to track two kinematic metrics, sweep area and smoothness, in chronic stroke survivors. We computed Pearson correlation coefficients when appropriate.ResultsCompared to a traditional optical system, both systems tracked with high accuracy during 3D reaching, with mean absolute errors of 1.00 ± 0.80 cm and 1.09 ± 0.51 cm for the IMU and Vive, respectively. Furthermore, both methods’ estimated kinematics highly agreed with each other (p < 0.01).ConclusionsThese methods may be useful for developing kinematic metrics to evaluate stroke rehabilitation outcomes in both laboratory and clinical environments.Trial RegistrationThe clinical trial (ClinicalTrial.gov ID: NCT03401762) was registered on January 17, 2018 (https://clinicaltrials.gov/ct2/show/NCT03401762) and posted on January 1, 2018. The trial is scheduled to be completed by August 2023. The trial was updated on December 2, 2020 and is currently recruiting.