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

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.

Effects of Different Finger Grips and Arm Positions on the Performance of Manipulating the Chinese Brush in Chinese Adolescents

This study aimed to investigate the effects of finger grip and wrist position on Chinese calligraphy handwriting (CCH). Thirty participants were recruited in the study and asked to manipulate the Chinese brush using two finger grip methods (three-finger grip and five-finger grip) and two wrist positions (suspended wrist and raised wrist). Three experimental writing tasks were applied to investigate writing stability, agility, and hand–eye coordination, and to evaluate the completion time (s), area of error (cm2), and error times. Subjective responses (arm aching level, ease of grip, exertion level, and comfort) regarding the four combinations of Chinese brush manipulation were measured. The results indicated significantly better performance with the three-finger grip for the stability and agility tests, and with the five-finger grip for the hand–eye coordination task. Using the suspended wrist position for CCH allowed better agility and hand–eye coordination than the raised wrist position. In consideration of the results of the four operational combinations, the three-finger grip with a suspended wrist position demonstrated the best performance in both objective and subjective measurements. It is recommended for application in the early learning stage. These findings can be considered when teaching Chinese brushes for beginners of CCH in schools.

Pronated Grip View With Wrist Deviation: A Pilot Study on the Effect on Ulnocarpal Relationships

Background We hypothesize that different positions of the wrist in the coronal plane makes the carpus susceptible to ulnar impaction. Methods We prospectively enrolled 10 adult volunteers and obtained fluoroscopic images of each wrist in 12 different positions using a standardized protocol. Distances from the ulna to the lunate (UL) and ulna to the triquetrum (UT) were digitally measured as was the portion of the lunate surface area that was uncovered (LUR) with wrist deviation. Results A wrist position of Pronation, Neutral Deviation, and Grip (P-ND-G) significantly shortened the ulnocarpal distance when compared to a position of Neutral Rotation, Neutral Deviation, and No Grip (NR-ND-NG). Radial deviation during pronation and gripping (Pronated, Radial Deviation, Gripping [P-RD-G]) resulted in the lowest mean UL distance (1.2 mm). UT distance was minimized by a position of ulnar deviation during a pronated grip (Pronated, Ulnar Deviation, Gripping [P-UD-G]) (3.1 mm). The lunate becomes more uncovered with radial deviation. Conclusion Radial deviation minimizes the UL distance while ulnar deviation minimizes the UT distance during a wrist position of pronation and gripping. Further, there is more proximal lunate surface area uncoverage during all positions of radial deviation compared to ulnar deviation.

Wrist Position Sense in Two Dimensions: Between-Hand Symmetry and Anisotropic Accuracy Across the Space

A deep investigation of proprioceptive processes is necessary to understand the relationship between sensory afferent inputs and motor outcomes. In this work, we investigate whether and how perception of wrist position is influenced by the direction along which the movement occurs. Most previous studies have tested Joint Position Sense (JPS) through 1 degree of freedom (DoF) wrist movements, such as flexion/extension (FE) or radial/ulnar deviation (RUD). However, the wrist joint has 3-DoF and many activities of daily living produce combined movements, requiring at least 2-DoF wrist coordination. For this reason, in this study, target positions involved movement directions that combined wrist flexion or extension with radial or ulnar deviation. The chosen task was a robot-aided Joint Position Matching (JPM), in which blindfolded participants actively reproduced a previously passively assumed target joint configuration. The JPM performance of 20 healthy participants was quantified through measures of accuracy and precision, in terms of both perceived target direction and distance along each direction of movement. Twelve different directions of movement were selected and both hands tested. The left and right hand led to comparable results, both target extents and directions were differently perceived according to the target direction on the FE/RUD space. Moreover, during 2-DoF combined movements, subjects’ perception of directions was impaired when compared to 1-DoF target movements. In summary, our results showed that human perception of wrist position on the FE/RUD space is symmetric between hands but not isotropic among movement directions.

Median nerve travel and deformation in the transverse carpal tunnel increases with chuck grip force and deviated wrist position

Background We assessed median nerve travel and deformation concurrently to better understand the influence of occupational risk factors on carpal tunnel dynamics, including forceful chuck gripping and deviated wrist positions. Methods Fourteen healthy right-hand dominant participants performed a chuck grip in 6 experimental conditions: two relative force levels (10% and 40% of maximum voluntary effort); three wrist positions (15° radial deviation, 0° neutral, 30° ulnar deviation). Chuck grip forces were measured with a load cell while the transverse cross-section of the carpal tunnel was imaged via ultrasound at the distal wrist crease. Images of the median nerve were analyzed in ImageJ to assess cross-sectional area, circularity, width, and height as well as travel in the anterior-posterior and medial-lateral axes. Results We found a main effect of deviated wrist position on both anterior-posterior and medial-lateral travel, with the greatest nerve travel occurring in 30° ulnar deviation. There was also a significant interaction between chuck grip force and deviated wrist position on cross-sectional area. Specifically, the area decreased with 40% vs. 10% chuck grip force when the wrist was in 30° ulnar deviation; however, there were no changes in 0° neutral and 15° radial deviation. Discussion Overall, we demonstrated that forceful chuck gripping in deviated wrist positions influenced carpal tunnel dynamics, resulting in both migratory and morphological changes to the median nerve. These changes may, in turn, increase local strain and stress with adjacent structures in the carpal tunnel. Future studies mapping contact stress between structures may further elucidate injury development of work-related carpal tunnel syndrome.

Estimation of arm kinematics in stroke survivors using wearable sensors

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.

Abstract P202: Estimation of Arm Kinematics in Stroke Survivors With Wearable Sensors

Introduction: Stroke is the leading cause of long-term disability in the US, often resulting in upper extremity (UE) motor impairment. Numerous clinical metrics have been developed and used to evaluate UE motor function to assess rehabilitation outcomes, but most of these are innately subjective and/or have relatively low sensitivity to change due to the use of ordinal scales. As a result, there is a growing interest in the use of kinematics to evaluate UE motor function, as they provide completely objective, high resolution quantitative measurements. However, obtaining kinematic measurements in stroke survivors can be a challenging task, as non-ideal environments (e.g., hospital rooms), expense, and a limited ability to perform calibration poses can make traditional optical tracking systems impractical. To overcome these challenges, we developed and compared two methods using different wearable sensors to estimate elbow angle and wrist position during reaching movements in people with stroke. Methods: We developed frameworks specific for two different types of sensors, inertial measurement units (IMU) and virtual reality (Vive) trackers, to estimate elbow angle and wrist position. We assessed each sensor’s estimation accuracy during pure flexion-extension motion, performed by a manual goniometer, and pure pronation-supination motion, performed by a healthy participant. We also compared each sensor’s ability to longitudinally track a stroke survivor’s UE function by using the wrist position estimates to compute sweep areas during a sweeping task. Results: For the IMUs, our results demonstrated accuracy to within 4.8° and 1.2 cm for elbow angle and wrist position, respectively. For the Vive, our results demonstrated accuracy to within 2.2° and 0.9 cm. The change in sweep area estimated by each method agreed with each other, as the difference between estimates was approximately 4% of the change in sweep area. Conclusion: These methods can be used to develop and accurately assess kinematic metrics for use in evaluating stroke rehabilitation outcomes.