Megan Kamachi - Academia.edu (original) (raw)

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Papers by Megan Kamachi

Research paper thumbnail of Development of an Automated Minimum Foot Clearance Measurement System: Proof of Principle

Sensors

Over half of older adult falls are caused by tripping. Many of these trips are likely due to obst... more Over half of older adult falls are caused by tripping. Many of these trips are likely due to obstacles present on walkways that put older adults or other individuals with low foot clearance at risk. Yet, Minimum Foot Clearance (MFC) values have not been measured in real-world settings and existing methods make it difficult to do so. In this paper, we present the Minimum Foot Clearance Estimation (MFCE) system that includes a device for collecting calibrated video data from pedestrians on outdoor walkways and a computer vision algorithm for estimating MFC values for these individuals. This system is designed to be positioned at ground level next to a walkway to efficiently collect sagittal plane videos of many pedestrians’ feet, which is then processed offline to obtain MFC estimates. Five-hundred frames of video data collected from 50 different pedestrians was used to train (370 frames) and test (130 frames) a convolutional neural network. Finally, data from 10 pedestrians was analy...

Research paper thumbnail of Reducing lumbar spine flexion using real-time biofeedback during patient handling tasks

Work

BACKGROUND: Patient handling activities require caregivers to adopt postures that increase the ri... more BACKGROUND: Patient handling activities require caregivers to adopt postures that increase the risk of back injury. Training programs relying primarily on didactic methods have been shown to be ineffective in reducing this risk. The use of real-time biofeedback has potential as an alternative training method. OBJECTIVE: To investigate the effect of real-time biofeedback on time spent by caregivers in end-range lumbar spine flexion. METHODS: Novice participants were divided into intervention (n = 10) and control (n = 10) groups and were asked to perform a set of simulated care activities eight times on two consecutive days. Individuals in the intervention group watched a training video on safer movement strategies and received real-time auditory feedback from a wearable device (PostureCoach) in four training trials whenever their lumbar spine flexion exceeded a threshold (70% of maximum flexion). Changes in end-range lumbar spine flexion were compared between groups and across trials. RESULTS: Participants in the intervention group saw reductions in end-range lumbar spine flexion during the simulated patient handling tasks at the end of the training compared to their baseline trials while there was no change for the control group. CONCLUSIONS: The training program including PostureCoach has the potential to help caregivers learn to use safer postures that reduce the risk of back injury.

Research paper thumbnail of Development of an Automated Minimum Foot Clearance Measurement System: Proof of Principle

Sensors

Over half of older adult falls are caused by tripping. Many of these trips are likely due to obst... more Over half of older adult falls are caused by tripping. Many of these trips are likely due to obstacles present on walkways that put older adults or other individuals with low foot clearance at risk. Yet, Minimum Foot Clearance (MFC) values have not been measured in real-world settings and existing methods make it difficult to do so. In this paper, we present the Minimum Foot Clearance Estimation (MFCE) system that includes a device for collecting calibrated video data from pedestrians on outdoor walkways and a computer vision algorithm for estimating MFC values for these individuals. This system is designed to be positioned at ground level next to a walkway to efficiently collect sagittal plane videos of many pedestrians’ feet, which is then processed offline to obtain MFC estimates. Five-hundred frames of video data collected from 50 different pedestrians was used to train (370 frames) and test (130 frames) a convolutional neural network. Finally, data from 10 pedestrians was analy...

Research paper thumbnail of Reducing lumbar spine flexion using real-time biofeedback during patient handling tasks

Work

BACKGROUND: Patient handling activities require caregivers to adopt postures that increase the ri... more BACKGROUND: Patient handling activities require caregivers to adopt postures that increase the risk of back injury. Training programs relying primarily on didactic methods have been shown to be ineffective in reducing this risk. The use of real-time biofeedback has potential as an alternative training method. OBJECTIVE: To investigate the effect of real-time biofeedback on time spent by caregivers in end-range lumbar spine flexion. METHODS: Novice participants were divided into intervention (n = 10) and control (n = 10) groups and were asked to perform a set of simulated care activities eight times on two consecutive days. Individuals in the intervention group watched a training video on safer movement strategies and received real-time auditory feedback from a wearable device (PostureCoach) in four training trials whenever their lumbar spine flexion exceeded a threshold (70% of maximum flexion). Changes in end-range lumbar spine flexion were compared between groups and across trials. RESULTS: Participants in the intervention group saw reductions in end-range lumbar spine flexion during the simulated patient handling tasks at the end of the training compared to their baseline trials while there was no change for the control group. CONCLUSIONS: The training program including PostureCoach has the potential to help caregivers learn to use safer postures that reduce the risk of back injury.

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