Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Miyake, Tetsuo; Yamamoto, Shozo; Hosono, Satoshi; Funabashi, Satoshi; Cheng, Zhengxue; Zhang, Cheng; Tamaki, Emi; Sugano, Shigeki

doi:10.3390/s21041081

Cited by 7 publications

(3 citation statements)

References 37 publications

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“…This study used a muscle deformation sensor array, FirstVR (H2L Inc., Tokyo, Japan), as shown in Figure 2 [15,16]. Image Credit: Author…”

Section: Equipment Used For Measurementsmentioning

confidence: 99%

Analyzing the Differences in the Degree of Force Application Between Novice and Expert Physiotherapists Using a Muscle Deformation Sensor

Shimabukuro,

Miyake,

Tamaki

2024

Cureus

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Background: Training physiotherapists require substantial experience and a lengthy period of time to achieve proficiency. However, establishing an objective method for quantifying the degree of force applied during treatment remains elusive, making training difficult.Objectives: This study aims to clarify the difference in the degree of force application between novice and expert physiotherapists using muscle deformation sensors and to assist in teaching.Methods: A muscle deformation sensor array was utilized to capture the muscle bulging (muscle deformation), and the degree of force was visualized. The experiment involved two types of physiotherapy: upper and lower extremity exercises. Subsequently, the muscle deformation value and standard deviations of the muscle deformation data obtained were compared.Results: Significant differences between novices and experts were observed in forearm muscle deformation values and standard deviations across both types of physiotherapies (p<0.05). Additionally, a distinction was observed in the left lower limb flexor muscles during upper extremity exercise (p<0.05). Conclusion:The results of this survey showed notable differences in the degree of force application between novices and experts, as demonstrated by our findings. Moreover, these implications extend beyond physiotherapy to sports, hobbies, and the teaching of traditional skills.

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“…This study used a muscle deformation sensor array, FirstVR (H2L Inc., Tokyo, Japan), as shown in Figure 2 [15,16]. Image Credit: Author…”

Section: Equipment Used For Measurementsmentioning

confidence: 99%

Analyzing the Differences in the Degree of Force Application Between Novice and Expert Physiotherapists Using a Muscle Deformation Sensor

Shimabukuro,

Miyake,

Tamaki

2024

Cureus

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“…Differential diagnosis of temporomandibular joint disorders using sEMG [ 115 ]. Gait Phase Detection [ 116 ]. Evaluation of sarcopenia based on sEMG platform [ 117 ].…”

Section: Figurementioning

confidence: 99%

A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications

Zheng

Zhao

et al. 2022

Biosensors

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Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.

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“…FirstVR was banded around the same part of the body as the placement of EMS pads. Infrared optical sensing observes the state of the muscle which is deformed corresponding to the motion of the endpoint of a limb (Miyake et al, 2021(Miyake et al, , 2019. The optical sensing method has resistance against sweating and can eliminate noise.…”

Section: Systemmentioning

confidence: 99%

Feedback Method of Force Controlled by Electrical Muscle Stimulation Based on Infrared Optical Sensing

Hosono¹,

Miyake²,

Miyake³

et al. 2022

Front. Virtual Real.

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The goal of the study was to develop a system that can adjust the electrical muscle stimulation parameters for individuals when sharing experiences with stimulation by sensing the degree of muscle contraction during electrical stimulation. If we do not know the appropriate amount of current for stimulation for an individual, the muscles would not contract as we aimed, and we will not be able to share the experience as we expected. In this study, we presented a system estimating fingertip force as the output of electrical muscle stimulation by monitoring the muscle state based on infrared optical sensing for adjusting electrical muscle stimulation parameters for the individual. We developed a regression model based on support vector regression during electrical stimulation using an infrared optical sensor with seven people's data to estimate the pushing force. The coefficient of determination between the measured pushing force and estimated pushing force was greater than 0.8 and 0.9 for the index and middle fingers, respectively. The system can monitor a feedback value of electrical muscle stimulation fingertip control. The system showed the feasibility of infrared optical sensing for the closed-loop feedback control system of the electrical stimulation parameters for an individual.

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Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Cited by 7 publications

References 37 publications

Analyzing the Differences in the Degree of Force Application Between Novice and Expert Physiotherapists Using a Muscle Deformation Sensor

Analyzing the Differences in the Degree of Force Application Between Novice and Expert Physiotherapists Using a Muscle Deformation Sensor

A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications

Feedback Method of Force Controlled by Electrical Muscle Stimulation Based on Infrared Optical Sensing

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