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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jeffrey Z. Nie ◽  
James W. Nie ◽  
Na-Teng Hung ◽  
R. James Cotton ◽  
Marc W. Slutzky
Keyword(s):  
Open Source ◽  
Tracking System ◽  
Wearable Sensors ◽  
Correlation Coefficients ◽  
Arm Movement ◽  
Optical Tracking ◽  
Optical Tracking System ◽  
Reaching Task ◽  
Rehabilitation Outcomes ◽  
Wrist Position

AbstractArm 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.

scholarly journals Estimation of arm kinematics in stroke survivors using wearable sensors

2021 ◽  
Author(s):  
Jeffrey Z. Nie ◽  
James W. Nie ◽  
Na-Teng Hung ◽  
R. James Cotton ◽  
Marc W. Slutzky
Keyword(s):  
Pearson Correlation ◽  
Wearable Sensors ◽  
Motor Impairment ◽  
Correlation Coefficients ◽  
The United States ◽  
Optical Tracking ◽  
Stroke Survivors ◽  
Reaching Task ◽  
Wrist Position ◽  
Arm Kinematics

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.

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

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Jeffrey Z Nie ◽  
James W Nie ◽  
Na-Teng Hung ◽  
Marc Slutzky
Keyword(s):  
Motor Function ◽  
Wearable Sensors ◽  
Motor Impairment ◽  
Optical Tracking ◽  
Estimation Accuracy ◽  
Stroke Survivors ◽  
Elbow Angle ◽  
Rehabilitation Outcomes ◽  
Wrist Position ◽  
Flexion Extension

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.

scholarly journals In Vitro and In Vivo Assessment of a New Workflow for the Acquisition of Mandibular Kinematics Based on Portable Tracking System with Passive Optical Reflective Markers

2021 ◽  
Vol 11 (9) ◽  
pp. 3947
Author(s):  
Marco Farronato ◽  
Gianluca M. Tartaglia ◽  
Cinzia Maspero ◽  
Luigi M. Gallo ◽  
Vera Colombo
Keyword(s):  
Measurement Error ◽  
Tracking System ◽  
Intraclass Correlation ◽  
Optical Tracking ◽  
Optical Tracking System ◽  
Rater Reliability ◽  
Tracking Device ◽  
Mandibular Kinematics

Clinical use of portable optical tracking system in dentistry could improve the analysis of mandibular movements for diagnostic and therapeutic purposes. A new workflow for the acquisition of mandibular kinematics was developed. Reproducibility of measurements was tested in vitro and intra- and inter-rater repeatability were assessed in vivo in healthy volunteers. Prescribed repeated movements (n = 10) in three perpendicular directions of the tracking-device coordinate system were performed. Measurement error and coefficient of variation (CV) among repetitions were determined. Mandibular kinematics of maximum opening, left and right laterality, protrusion and retrusion of five healthy subjects were recorded in separate sessions by three different operators. Obtained records were blindly examined by three observers. Intraclass correlation coefficient (ICC) was calculated to estimate inter-rater and intra-rater reliability. Maximum in vitro measurement error was 0.54 mm and CV = 0.02. Overall, excellent intra-rater reliability (ICC > 0.90) for each variable, general excellent intra-rater reliability (ICC = 1.00) for all variables, and good reliability (ICC > 0.75) for inter-rater tests were obtained. A lower score was obtained for retrusion with “moderate reliability” (ICC = 0.557) in the inter-rater tests. Excellent repeatability and reliability in optical tracking of primary movements were observed using the tested portable tracking device and the developed workflow.

scholarly journals High Precision Optical Tracking System Based on near Infrared Trinocular Stereo Vision

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2528
Author(s):  
Songlin Bi ◽  
Yonggang Gu ◽  
Jiaqi Zou ◽  
Lianpo Wang ◽  
Chao Zhai ◽  
...  
Keyword(s):  
High Precision ◽  
Stereo Vision ◽  
Near Infrared ◽  
Nearest Neighbor ◽  
Tracking System ◽  
Optical Tracking ◽  
Tracking Accuracy ◽  
Optical Tracking System ◽  
Dynamic Tracking ◽  
Trinocular Stereo

A high precision optical tracking system (OTS) based on near infrared (NIR) trinocular stereo vision (TSV) is presented in this paper. Compared with the traditional OTS on the basis of binocular stereo vision (BSV), hardware and software are improved. In the hardware aspect, a NIR TSV platform is built, and a new active tool is designed. Imaging markers of the tool are uniform and complete with large measurement angle (>60°). In the software aspect, the deployment of extra camera brings high computational complexity. To reduce the computational burden, a fast nearest neighbor feature point extraction algorithm (FNNF) is proposed. The proposed method increases the speed of feature points extraction by hundreds of times over the traditional pixel-by-pixel searching method. The modified NIR multi-camera calibration method and 3D reconstruction algorithm further improve the tracking accuracy. Experimental results show that the calibration accuracy of the NIR camera can reach 0.02%, positioning accuracy of markers can reach 0.0240 mm, and dynamic tracking accuracy can reach 0.0938 mm. OTS can be adopted in high-precision dynamic tracking.

scholarly journals Skill Transference of a Probe-Tube Placement Training Simulator

2020 ◽  
Vol 31 (01) ◽  
pp. 040-049 ◽  
Author(s):  
Robert W. Koch ◽  
Hasan Saleh ◽  
Paula Folkeard ◽  
Sheila Moodie ◽  
Conner Janeteas ◽  
...  
Keyword(s):  
Mixed Model ◽  
Tracking System ◽  
Optical Tracking ◽  
Tube Placement ◽  
Control Group ◽  
Educational Settings ◽  
Training Simulator ◽  
Nonlinear Mixed Model ◽  
Optical Tracking System ◽  
Clinical Scenarios

AbstractProbe-tube placement is a necessary step in hearing aid verification which needs ample hands-on experience and confidence before performing in clinic. To improve the methods of training in probe-tube placement, a manikin-based training simulator was developed consisting of a 3D-printed head, a flexible silicone ear, and a mounted optical tracking system. The system is designed to provide feedback to the user on the depth and orientation of the probe tube, and the time required to finish the task. Although a previous validation study was performed to determine its realism and teachability with experts, further validation is required before implementation into educational settings.This study aimed to examine the skill transference of a newly updated probe-tube placement training simulator to determine if skills learned on this simulator successfully translate to clinical scenarios.All participants underwent a pretest in which they were evaluated while performing a probe-tube placement and real-ear-to-coupler difference (RECD) measurement on a volunteer. Participants were randomized into one of two groups: the simulator group or the control group. During a two-week training period, all participants practiced their probe-tube placement according to their randomly assigned group. After two weeks, each participant completed a probe-tube placement on the same volunteer as a posttest scenario.Twenty-five novice graduate-level student clinicians.Participants completed a self-efficacy questionnaire and an expert observer completed a questionnaire evaluating each participant’s performance during the pre- and posttest sessions. RECD measurements were taken after placing the probe tube and foam tip in the volunteer’s ear. Questionnaire results were analyzed through nonparametric t-tests and analysis of variance, whereas RECD results were analyzed using a nonlinear mixed model method.Results suggested students in the simulator group were less likely to contact the tympanic membrane when placing a probe tube, appeared more confident, and had better use of the occluding foam tip, resulting in more improved RECD measurements.The improved outcomes for trainees in the simulator group suggest that supplementing traditional training with the simulator provides useful benefits for the trainees, thereby encouraging its usage and implementation in educational settings.

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