Development of a Wearable Motion Analysis System for Evaluation and Rehabilitation of Mild Traumatic Brain Injury (mTBI)

2012 ◽  
Author(s):  
Stephanie L. Carey ◽  
Kevin Hufford ◽  
Amanda Martori ◽  
Mario Simoes ◽  
Francy Sinatra ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Brain Injuries ◽  
Training Session ◽  
Motion Analysis System ◽  
Laboratory Setting ◽  
Inertial Measurement ◽  
Gait Parameters ◽  
Measurement Units ◽  
Analysis System ◽  
Set Up

Mild traumatic brain injuries (mTBI) stem from a number of causes such as illnesses, strokes, accidents or battlefield traumas. These injuries can cause issues with everyday tasks, such as gait, and are linked with vestibular dysfunction [1]. Current technology that measures gait parameters often requires time consuming set up and post processing and is limited to the laboratory setting. The purpose of this study was to develop a wearable motion analysis system (WMAS) using five commercially available inertial measurement units (IMU) working in unison to record and output four gait parameters in a clinically relevant way. The WMAS has the potential to be used to 1) help diagnose mTBI or other neurocognitive disorders; 2) provide feedback to a clinician during a training session; 3) collect gait parameter data outside of the laboratory setting to determine rehabilitation progress; 4) provide quantitative outcome measures for rehabilitation efficacy.

Knee Angle Analysis Using a Wearable Motion Analysis System for Detection and Rehabilitation of Mild Traumatic Brain Injury

2013 ◽  
Author(s):  
Amanda L. Martori ◽  
Stephanie L. Carey ◽  
Derek J. Lura ◽  
Rajiv V. Dubey
Keyword(s):  
Motion Analysis ◽  
Brain Injuries ◽  
Wearable Sensors ◽  
Motion Analysis System ◽  
Laboratory Setting ◽  
Gait Parameters ◽  
Optical Motion ◽  
Football Field ◽  
Analysis System ◽  
Optical Motion Capture

Mild traumatic brain injuries (mTBI) are common in soldiers and athletes, and can affect many areas of a person’s daily life including gait [1]. Current methods of measuring gait parameters involve expensive optical motion capture systems, time intensive setup, wires, complicated filtering techniques, and a laboratory setting. A wearable and wireless motion analysis system would allow gait analysis to be performed outside of a laboratory setting during activities of daily living, in a clinical setting or on a football field. The purpose of this study was to develop and verify an algorithm to calculate knee flexion during slow gait, particularly during terminal stance and pre-swing phases, using wireless wearable sensors.

scholarly journals Can We Accurately Measure Axial Segment Coordination during Turning Using Inertial Measurement Units (IMUs)?

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2518 ◽  
Author(s):  
Fuengfa Khobkhun ◽  
Mark A. Hollands ◽  
Jim Richards ◽  
Amornpan Ajjimaporn
Keyword(s):  
Motion Analysis ◽  
Movement Disorders ◽  
Clinical Settings ◽  
Motion Analysis System ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Measurement Units ◽  
Analysis System

Camera-based 3D motion analysis systems are considered to be the gold standard for movement analysis. However, using such equipment in a clinical setting is prohibitive due to the expense and time-consuming nature of data collection and analysis. Therefore, Inertial Measurement Units (IMUs) have been suggested as an alternative to measure movement in clinical settings. One area which is both important and challenging is the assessment of turning kinematics in individuals with movement disorders. This study aimed to validate the use of IMUs in the measurement of turning kinematics in healthy adults compared to a camera-based 3D motion analysis system. Data were collected from twelve participants using a Vicon motion analysis system which were compared with data from four IMUs placed on the forehead, middle thorax, and feet in order to determine accuracy and reliability. The results demonstrated that the IMU sensors produced reliable kinematic measures and showed excellent reliability (ICCs 0.80–0.98) and no significant differences were seen in paired t-tests in all parameters when comparing the two systems. This suggests that the IMU sensors provide a viable alternative to camera-based motion capture that could be used in isolation to gather data from individuals with movement disorders in clinical settings and real-life situations.

A Simple 2D Wheelchair Positioning: Correcting IMU’s Data Using One Encoder and Applying Kalman Filtering

2013 ◽  
Author(s):  
Zohreh Salimi ◽  
Martin W. Ferguson-Pell
Keyword(s):  
Kalman Filtering ◽  
Good Accuracy ◽  
Wheelchair Propulsion ◽  
Motion Analysis System ◽  
Inertial Measurement ◽  
Signal Drift ◽  
Stationary Test ◽  
Measurement Units ◽  
Analysis System ◽  
Spatial Positioning

Inertial Measurement Units (IMU) are widely used for spatial positioning. They are well known, however, for signal drift. A common way of overcoming the drift is to use Kalman Filtering. In this study, we have undertaken some experiments during wheelchair propulsion, recording data with an IMU, an Encoder (tachometer) and an Optotrak (motion analysis system). We then applied Kalman filtering (with two approaches) to IMU’s data. Eventually, in order to verify Kalman’s results, they were compared to Optotrak’s data. As result of this study, 2D wheelchair tracking can be done with acceptable precision, using one IMU and one Encoder and applying Kalman filtering. Kalman filtering with approach B was a better predictor of subject’s spatial position than approach A. Kalman and even IMU’s results for rotation were of good accuracy; therefore IMU’s data can be used to find all angular characteristics of subject’s position, even without applying Kalman filtering, if the offsets are precisely found through a stationary test.

scholarly journals Agreement Between the Spatiotemporal Gait Parameters of Healthy Adults From the OptoGait System and a Traditional Three-Dimensional Motion Capture System

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Aoife Healy ◽  
Kimberley Linyard-Tough ◽  
Nachiappan Chockalingam
Keyword(s):  
Motion Analysis ◽  
Motion Capture ◽  
Intraclass Correlation ◽  
Three Dimensional ◽  
Healthy Adults ◽  
Systematic Bias ◽  
Motion Analysis System ◽  
Motion Capture System ◽  
Gait Parameters ◽  
Analysis System

While previous research has assessed the validity of the OptoGait system to the GAITRite walkway and an instrumented treadmill, no research to date has assessed this system against a traditional three-dimensional motion analysis system. Additionally, previous research has shown that the OptoGait system shows systematic bias when compared to other systems due to the configuration of the system's hardware. This study examined the agreement between the spatiotemporal gait parameters calculated from the OptoGait system and a three-dimensional motion capture (14 camera Vicon motion capture system and 2 AMTI force plates) in healthy adults. Additionally, a range of filter settings for the OptoGait were examined to determine if it was possible to eliminate any systematic bias between the OptoGait and the three-dimensional motion analysis system. Agreement between the systems was examined using 95% limits of agreement by Bland and Altman and the intraclass correlation coefficient. A repeated measure ANOVA was used to detect any systematic differences between the systems. Findings confirm the validity of the OptoGait system for the evaluation of spatiotemporal gait parameters in healthy adults. Furthermore, recommendations on filter settings which eliminate the systematic bias between the OptoGait and the three-dimensional motion analysis system are provided.

scholarly journals Validity of Measurement for Trailing Limb Angle and Propulsion Force during Gait Using a Magnetic Inertial Measurement Unit

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Takasuke Miyazaki ◽  
Masayuki Kawada ◽  
Yuki Nakai ◽  
Ryoji Kiyama ◽  
Kazunori Yone
Keyword(s):  
Lumbar Spine ◽  
Motion Analysis ◽  
Reaction Force ◽  
Measurement Unit ◽  
Lumbar Region ◽  
Motion Analysis System ◽  
Inertial Measurement ◽  
Propulsion Force ◽  
Trailing Limb Angle ◽  
Analysis System

Propulsion force and trailing limb angle (TLA) are meaningful indicators for evaluating quality of gait. This study examined the validity of measurement for TLA and propulsion force during various gait conditions using magnetic inertial measurement units (IMU), based on measurements using a three-dimensional motion analysis system and a force platform. Eighteen healthy males (mean age 25.2  ±  3.2 years, body height 1.70   ±  0.06 m) walked with and without trunk fluctuation at preferred, slow, and fast velocities. IMU were fixed on the thorax, lumbar spine, and right thigh and shank. IMU calculated the acceleration and tilt angles in a global coordinate system. TLA, consisting of a line connecting the hip joint with the ankle joint, and the laboratory’s vertical axis at late stance in the sagittal plane, was calculated from thigh and shank segment angles obtained by IMU, and coordinate data from the motion analysis system. Propulsion force was estimated by the increment of velocity calculated from anterior acceleration measured by IMU fixed on the thorax and lumbar spine, and normalized impulse of the anterior component of ground reaction force (AGRF) during late stance. Similarity of TLA measured by IMU and the motion analysis system was tested by the coefficient of multiple correlation (CMC), intraclass correlation coefficient (ICC), and root mean square (RMS) of measurement error. Relationships between normalized impulse of AGRF and increments of velocity, as measured by IMU, were tested using correlation analysis. CMC of TLA was 0.956–0.959. ICC between peak TLAs was 0.831–0.876 (p<0.001), and RMS of error was 1.42°–1.92°. Velocity increment calculated from acceleration on the lumbar region showed strong correlations with normalized impulse of AGRF (r=0.755–0.892, p<0.001). These results indicated a high validity of estimation of TLA and propulsion force by IMU during various gait conditions; these methods would be useful for best clinical practice.

THE USE OF MOTION ANALYSIS SYSTEM AND ORTHOSIS IN PATIENTS WITH NEURO-MUSCULOSKELETAL DISORDERS

2014 ◽  
Vol 14 (02) ◽  
pp. 1450028 ◽  
Author(s):  
MOHAMMAD TAGHI KARIMI ◽  
JAVID MOSTAMAND ◽  
FRANCIS FATOYE
Keyword(s):  
Knee Joint ◽  
Musculoskeletal Disorders ◽  
Motion Analysis ◽  
Hip Joint ◽  
Motion Analysis System ◽  
Flat Foot ◽  
Gait Parameters ◽  
Significant Difference ◽  
Joint Monitoring ◽  
Analysis System

Background: Neuro-musculoskeletal disorders are a major source of physical disability involving more than one joint. Monitoring all joints during walking is achieved by using motion analysis system. There is limited evidence to show the suitability of motion analysis system to monitor neuro-musculoskeletal disorders. This research investigated the feasibility of this system to represent in patients with neuro-musculoskeletal disorders during walking. Method: Five groups of normal subjects with: knee osteoarthritis; avascular necrosis of hip joint; spinal cord injury and flat foot were recruited into this study. Kinetic and kinematic parameters were obtained by the use of motion analysis (Qualysis with seven cameras) and a Kistler force platform. The differences between gait parameters of normal and subjects with these disorders were examined using the independent t-tests. Paired t-test analysis was also used to determine the difference between walking with and without orthosis. Significant value was set at p ≤ 0.05. Results: There was a significant difference between the moment applied on the knee joint, the integral area between center of pressure (COP) and center of knee joint (COJ) graphs of normal and osteoarthritis (OA) subjects (p < 0.05). The area between COP and COJ of the ankle joint significantly differed between normal and flat foot subjects (p < 0.05). However, the force transmitted through the hip joint in subjects with Perthes did not differ significantly while walking with and without orthosis. In paraplegic subjects, the force applied on the limb and the mean values of gait parameters varied while walking with different orthoses which showed the feasibility of the system to monitor the performance of subjects with SCI disorder. Conclusion: The findings of the present study imply that the use of motion analysis is feasibility for assessing and monitoring neuro-musculoskeletal disorders. However, different parameters should be selected for various neuro-musculoskeletal disorders.

scholarly journals Estimation of Spatial-Temporal Gait Parameters Using a Low-Cost Ultrasonic Motion Analysis System

Sensors ◽  
2014 ◽  
Vol 14 (8) ◽  
pp. 15434-15457 ◽  
Author(s):  
Yongbin Qi ◽  
Cheong Soh ◽  
Erry Gunawan ◽  
Kay-Soon Low ◽  
Rijil Thomas
Keyword(s):  
Motion Analysis ◽  
Low Cost ◽  
Motion Analysis System ◽  
Gait Parameters ◽  
Analysis System
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