Perception Accuracy of Vibrotactile Feedback during Locomotion

Demircan, Emel; Recinos, Elliot; Abella, John R.; Khoo, I‐Hung; Teng, Sharon; Wu, Will

doi:10.1109/urai.2019.8768771

Cited by 6 publications

(6 citation statements)

References 26 publications

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“…The subject was instructed to increase foot-drop angle when they experienced continuous vibrations and reduce footdrop angle when they experienced staggered vibrations while they were running. The technical specifications of the haptic feedback system and vibration types were introduced in our recent study [69].…”

Section: Haptic Feedback Systemmentioning

confidence: 99%

“…The subject experienced combinations of 2 types haptic feedback as follows: torso and knees (increase/decrease trunk lean and increase/ decrease cadence), torso and ankles (increase/decrease trunk lean and increase/decrease foot drop angle), and knees and ankles (increase/decrease cadence and increase/decrease foot drop angle) during each run of the second feedback session. Vibrations were sent in either continuous or staggered mode [69] to indicate the subject must increase or decrease the kinematic variable of interest. The subject was asked to try to maintain a posture and pace that resulted in no haptic feedback for a total of 15 s. The subject ran a maximum of 15.5 min throughout the experiment.…”

Section: Motion Trainingmentioning

confidence: 99%

“…This provide us with preliminary results to understand the effect of real-time vibrotactile feedback to elicit motor adaptation in locomotion. This work builts upon on our recent results on human perception accuracy of vibrotactile feedback during locomotion [69]. In addition, a novel simulation framework for motion tracking and analysis is introduced.…”

Section: Introductionmentioning

confidence: 99%

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A pilot study on locomotion training via biomechanical models and a wearable haptic feedback system

Demircan

2020

Robomech J

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Locomotion is a fundamental human skill. Real-time sensing and feedback is a promising strategy for motion training to reconstruct healthy locomotion patterns lost due to aging or disease, and to prevent injuries. In this paper, we present a pilot study on locomotion training via biomechanical modeling and a wearable haptic feedback system. In addition, a novel simulation framework for motion tracking and analysis is introduced. This unified framework, implemented within the Unity environment, is used to analyze subject's baseline and performance characteristics, and to provide real-time haptic feedback during locomotion. The framework incorporates accurate musculoskeletal models derived from OpenSim, closed-form calculations of muscle routing kinematics and kinematic Jacobian matrices, dynamic performance metrics (i.e., muscular effort), human motion reconstruction via inertial measurement unit (IMU) sensors, and real-time visualization of the motion and its dynamics. A pilot study was conducted in which 6 healthy subjects learned to alter running patterns to lower the knee flexion moment (KFM) through haptic feedback. We targeted three gait parameters (trunk lean, cadence, and foot strike) that previous studies had identified as having an influence on reducing the knee flexion moment and associated with increased risk of running injuries. All subjects were able to adopt altered running patterns requiring simultaneous changes to these kinematic parameters and reduced their KFM to 30-85% of their baseline values. The muscular effort during motion training stayed comparable to subjects' baseline. This study shows that biomechanical modeling, together with real-time sensing and wearable haptic feedback can greatly increase the efficiency of motion training.

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Section: Haptic Feedback Systemmentioning

confidence: 99%

Section: Motion Trainingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A pilot study on locomotion training via biomechanical models and a wearable haptic feedback system

Demircan

2020

Robomech J

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“…Our study is an extension of work originally presented in IEEE International Conference on Ubiquitous Robots (URAI 2019) [1]. Here, we provide a more comprehensive understanding of human interpretation of vibrotactile feedback during walking and running, including the effect of feedback locations.…”

Section: Introductionmentioning

confidence: 91%

“…This paper is an extension of work originally presented in IEEE International Conference on Ubiquitous Robots (URAI 2019) [1]. A key in quantifying and improving locomotion is identification of useful, tractable metrics and providing useful feedback.…”

Section: Introductionmentioning

confidence: 95%

Understanding Human Perception of Vibrotactile Feedback in Walking and Running Tasks

Demircan¹,

Khoo²,

Teng³

et al. 2020

Adv. sci. technol. eng. syst. j.

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Vibrotactile feedback is increasingly becoming an essential feedback component in several non-medical and medical areas. One area that vibrotactile feedback has not been explored as an intervention tool is in sports science. In addition, vibrotactile feedback lacks scientific evidence as a feedback mechanism within the sports world. A portable vibrotactile feedback system was developed to understand how a human perceives vibrotactile feedback while performing walking and running tasks. The system incorporates a model-based simulation framework to check human motion and visualize key performance metrics. We performed a pilot study on twenty-six subjects to understand the accuracy of human perception of vibrotactile feedback using the system we developed. Here, we investigated the type, number, and location of haptic feedbacks that would yield better subject perceived accuracy during walking and running. Findings suggested that staggered vibrotactile feedback would lead to higher accuracy than continuous vibrotactile feedback especially when more than two motors were used. For the subjects perception accuracy for all motor combinations, we observed an average that was 9.3% higher for walking compared to running. For one motor, the perception accuracy decreased by only 3.38% while running compared to walking. The decrease was much more significant for higher combinations of motors. The decrease in the perception accuracy of the motor locations was significantly less for both staggered (p < 0.001) and one motor (p < 0.001) vibration modes.

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Improving virtual reality navigation tasks using a haptic vest and upper body tracking

Monica

Aleotti

2023

Displays

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Perception Accuracy of Vibrotactile Feedback during Locomotion

Cited by 6 publications

References 26 publications

A pilot study on locomotion training via biomechanical models and a wearable haptic feedback system

A pilot study on locomotion training via biomechanical models and a wearable haptic feedback system

Understanding Human Perception of Vibrotactile Feedback in Walking and Running Tasks

Improving virtual reality navigation tasks using a haptic vest and upper body tracking

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