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

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.

Assessing the validity of inertial measurement units for shoulder kinematics using a commercial sensor‐software system: A validation study

“…On the other hand, camera‐based motion capture (Mocap) is still referenced as the gold standard for kinematic assessments of upper limb segments due to its high accuracy. 17 , 18 , 19 , 20 , 21 , 22 Yet, these systems may not be suitable for clinical practice since they require a large amount of preparation time, experienced operators, and a laboratory environment to achieve valid results. A promising alternative to objectively quantify body kinematics are portable devices such as inertial measurement units (IMU).…”

Myoelectric interface for neurorehabilitation conditioning to reduce abnormal leg co-activation after stroke: a pilot study

“…For the hip angle, an IMU sensor was placed over the anterior superior iliac spine (ASIS). Using the IMUs and the measured limb lengths to create a kinematic chain model [ 31 ] representing the lower extremity, we calculated the 3D orientation of the leg and estimated the knee flexion angle. The IMUs over the ASIS and lateral epicondyle were used similarly to estimate the hip abduction angle.…”

Computer-assisted approaches for measuring, segmenting, and analyzing functional upper extremity movement: a narrative review of the current state, limitations, and future directions

“…Wearable IMUs have been studied extensively by the movement science community ( 17 , 24 , 25 , 49 , 50 , 72 – 74 , 78 , 86 ). Although kinematics from the IMUs in isolation can be used (e.g., motion of the wrist-worn IMU), multiple IMUs attached to the body are used for pose estimation due to sensors being low cost and not suffering from issues associated with occlusion.…”

“…Although kinematics from the IMUs in isolation can be used (e.g., motion of the wrist-worn IMU), multiple IMUs attached to the body are used for pose estimation due to sensors being low cost and not suffering from issues associated with occlusion. IMUs have been assessed to be suitable for estimating UE kinematics in the laboratory and clinical settings ( 24 , 50 , 74 ), but there are challenges associated with widespread usage outside of these controlled settings.…”

“…For adoption in healthcare applications involving UEFAs, test-retest reliability ( 50 , 68 , 70 , 96 ) and validity ( 24 , 50 , 59 , 66 , 68 ) need to be assessed. Furthermore, accuracy assessments ( 25 , 63 , 64 , 67 , 73 , 74 , 78 ) that do not rely solely on healthy participants ( 17 , 38 ) are needed. Although the reviewed pose estimation methods are finding utility in health applications related to measuring UE movement, more widespread adoption of these tools require further assessments of measurement accuracy, validity, and reliability ( 9 ) on quantities that are important to movement scientists ( 38 ), e.g., joint angle ( 17 – 21 , 50 , 62 ).…”