A Motion Recognition Method Using Foot Pressure Sensors

Ohnishi, Ayumi; Terada, Tsutomu; Tsukamoto, Masahiko

doi:10.1145/3174910.3174938

Cited by 12 publications

(2 citation statements)

References 11 publications

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“…To apply the system in a pervasive way, a nonvision sensor, such as an inertial device, attached to the specific position of the body has also been widely used [ 15 ]. Additionally, some signals that can effectively reflect the variation of the body’s movement can also be adopted for motion estimation, such as the surface electrocardiogram signal of the forearm [ 20 ] and foot pressure [ 21 ]. A change of scenario can also be effectively adopted for motion recognition, such as using the infrared sensor to detect temperature changes [ 22 ], distance sensors for capturing the distance between the equipment and object [ 23 ], pressure-sensitive devices mounted on the floor, EEG signal [ 24 ], ambient light to estimate gestures [ 25 ], and utilization of Wi-Fi, RF signals [ 26 ], and so on.…”

Section: Related Workmentioning

confidence: 99%

Optimizing Sensor Position with Virtual Sensors in Human Activity Recognition System Design

Xia

Sugiura

2021

Sensors

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Human activity recognition (HAR) systems combined with machine learning normally serve users based on a fixed sensor position interface. Variations in the installing position will alter the performance of the recognition and will require a new training dataset. Therefore, we need to understand the role of sensor position in HAR system design to optimize its effect. In this paper, we designed an optimization scheme with virtual sensor data for the HAR system. The system is able to generate the optimal sensor position from all possible locations under a given sensor number. Utilizing virtual sensor data, the training dataset can be accessed at low cost. The system can help the decision-making process of sensor position selection with great accuracy using feedback, as well as output the classifier at a lower cost than a conventional training model.

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Section: Related Workmentioning

confidence: 99%

Optimizing Sensor Position with Virtual Sensors in Human Activity Recognition System Design

Xia

Sugiura

2021

Sensors

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“…However, we believe the sitting posture variations should reflect from the foot posture and motion variations. In literature, smart insoles has been used to detect postures unobtrusively [23,79]. Hence, a smart insole-based solution could be a practical and unobtrusive solution to identify stress that is induced by body language, such as through tracking leg movements and posture characteristics.…”

Section: Conceptmentioning

confidence: 99%

StressFoot: Uncovering the Potential of the Foot for Acute Stress Sensing in Sitting Posture

Elvitigala

Matthies

Nanayakkara

2020

Sensors

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Stress is a naturally occurring psychological response and identifiable by several body signs. We propose a novel way to discriminate acute stress and relaxation, using movement and posture characteristics of the foot. Based on data collected from 23 participants performing tasks that induced stress and relaxation, we developed several machine learning models to construct the validity of our method. We tested our models in another study with 11 additional participants. The results demonstrated replicability with an overall accuracy of 87%. To also demonstrate external validity, we conducted a field study with 10 participants, performing their usual everyday office tasks over a working day. The results showed substantial robustness. We describe ten significant features in detail to enable an easy replication of our models.

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Seamless-walk: natural and comfortable virtual reality locomotion method with a high-resolution tactile sensor

et al. 2023

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A Motion Recognition Method Using Foot Pressure Sensors

Cited by 12 publications

References 11 publications

Optimizing Sensor Position with Virtual Sensors in Human Activity Recognition System Design

Optimizing Sensor Position with Virtual Sensors in Human Activity Recognition System Design

StressFoot: Uncovering the Potential of the Foot for Acute Stress Sensing in Sitting Posture

Seamless-walk: natural and comfortable virtual reality locomotion method with a high-resolution tactile sensor

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