Ambulatory Measurement and Estimation of Joint Angle Kinematics in Sagittal Plane Using Body Worn Sensors for Gait Analysis

Patel, Gunjanbhai; Ojha, Rajdeep; Sujatha, S.

doi:10.1109/wispnet.2018.8538548

Cited by 2 publications

(4 citation statements)

References 13 publications

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“…A previously reported sensor fusion method (complementary algorithm) was used wherein the accelerometer data was passed through a low-pass filter and the gyroscope data was passed through an integrator followed by a high-pass filter. 47 The alpha variable related to the time-constant in the complementary algorithm was defined dynamically as a very high value (close to 1) for the gyroscope data and as a very low value (close to 0) for the accelerometer data. The resultant post-processed filtered accelerometer and gyroscope data were merged using sensor fusion method for knee joint angle estimation.…”

Section: Methodsmentioning

confidence: 99%

“…The gait analysis protocol established for the indoor and outdoor environment during the pilot phase of the study was followed. 47 Participants were instructed to stand straight at the start and finish point for 3 s during each gait trial session for collecting offset data from the i-Sens system in addition to walking data. Participants were asked to walk at self-selected speed on 10 m walkway in the indoor environment and 50 m (25 m back and forth) in the outdoor environment for gait data.…”

Section: Methodsmentioning

confidence: 99%

“…Previously, a body-worn inertial sensor (i-Sens)-based prototype was designed with custom embedded software and was used in indoor-outdoor environments for measurement of STPs and estimation of joint kinematics in the sagittal plane. 47 The i-Sens system overcomes integration drift errors 48 that limit the use of inertial sensor-based systems to short durations of gait analysis, by using a simplified sensor fusion algorithm (which is computationally better than kinematical reset drift correction method 44 ). The i-Sens system does not depend on the orientation and alignment of body-segments because the baseline standing position is negated each time data is captured.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

Patel

Mullerpatan

Agarwal

et al. 2022

Proc Inst Mech Eng H

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Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( n = 15) and outdoor ( n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson’s correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the “Good” category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

Patel

Mullerpatan

Agarwal

et al. 2022

Proc Inst Mech Eng H

Self Cite

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“…L. i-sens system inertial sensor (i-Sens) (triaxle accelerometer, gyroscope sensors) [17] Body-Worn Sensors for Gait Analysis: Ambulatory Measurement and Estimation of Joint Angle Kinematics in the Sagittal Plane provide an innovative wearable instrument based on wireless inertial sensors (i-Sens) for measuring joint angles in the sagittal plane. An accelerometer, gyroscope, microprocessor, and Bluetooth module make up the i-Sens hardware.…”

Section: K Penologist Technologymentioning

confidence: 99%

Review on Wearable Sensors of the Medical System

2023

IJSER

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A framework known as "smart healthcare" makes use of technologies like wearable's, and the Internet of Medical Things (IoT), In order to intelligently manage and respond to the needs of the health environment, we need to combine data, machine learning algorithms, wireless communication technology, and the Internet of Things (IoT) to link people, resources, and organizations; make health records easily accessible; and share the data widely. Medical sensors, or IoT, are one of the key components of smart healthcare. Due to the complexity of illnesses, Disease diagnosis often necessitates the use of multiple types of medical signals. The most crucial concern when employing multimodal signals is how to fuse them, which is a topic of growing interest among researchers. The newest generation of personal portable gadgets for telemedicine practice is wearable health monitoring systems. However, due to the inapplicability of the building process used for standard semiconductor equipment, wearable healthcare equipment research and commercialization are currently progressing at a very sluggish rate. Despite these obstacles, developments in materials flag, chemical analysis techniques, apparatus, and manufacturing processes created a groundwork for whole new wearable technology, which has continued to evolve.

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Ambulatory Measurement and Estimation of Joint Angle Kinematics in Sagittal Plane Using Body Worn Sensors for Gait Analysis

Cited by 2 publications

References 13 publications

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

Review on Wearable Sensors of the Medical System

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