The Piezo-resistive MC Sensor is a Fast and Accurate Sensor for the Measurement of Mechanical Muscle Activity

Meglič, Andrej; Uršič, Mojca; Škorjanc, Aleš; Đorđević, Srđan; Belušič, Gregor

doi:10.3390/s19092108

Cited by 10 publications

(3 citation statements)

References 38 publications

(47 reference statements)

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“…[23,[60][61][62] In contrast, although there is growing research investigating alternative approaches sensitive to peak radial displacement. [63] , their reliability is difficult to quantify, due to challenges such as maintaining consistent reaction forces or isolating sensors from mechanical coupling effects. [26,33] As for surface strain, although, like surface curvature, it can be easily measured with current wearable sensing technology, its high sensitivity, in both correlation and range, to variations in joint angle or measurement location (Figures 3B and 5) may limit its practicality in future wearables based on our findings.…”

Section: Discussionmentioning

confidence: 99%

Surface‐Level Muscle Deformation as a Correlate for Joint Torque

Alvarez,

de Marcillac,

Jin

et al. 2024

Adv Materials Technologies

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Wearable technology excels in estimating kinematic and physiological data, but estimating biological torques remains an open challenge. Deformation of the skin above contracting muscles—surface‐level muscle deformation—has emerged as a promising signal for joint torque estimation. However, a lack of ground‐truth measures of surface‐level muscle deformation has complicated the evaluation of wearable sensors designed to measure surface‐level muscle deformation. A non‐contact methodology is proposed for ground‐truth measurement of surface‐level muscle deformation using a 2D laser profilometer. It shows how three metrics of surface‐level muscle deformation—peak radial displacement: r = 0.94 ± 0.05, surface curvature: r = 0.78 ± 0.10, surface strain: r = 0.83 ± 0.12—correlate strongly to changes in volitional elbow torque, further exploring the impact of measurement location or joint angle on these relationships. A nonlinear, lead‐lag relationship between surface‐level muscle deformation and torque is also found. The findings suggest that surface‐level muscle deformation is a promising signal for non‐invasive, real‐time estimates of torque. By standardizing measurement, the methodology can help inform the design of future wearable sensors.

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Section: Discussionmentioning

confidence: 99%

Surface‐Level Muscle Deformation as a Correlate for Joint Torque

Alvarez,

de Marcillac,

Jin

et al. 2024

Adv Materials Technologies

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“…These sensors, which can be classified into resistive [ 10 ], piezoelectric [ 11 ], capacitive [ 12 ], and triboelectric [ 13 ] types based on their sensing mechanisms, play a crucial role in detecting tensile force, pressure, and other parameters [ 14 ]. Among these, resistive sensors have garnered widespread attention due to their relatively simple working mechanism, feasible fabrication processes, and ease of signal collection [ 15 ]. Strain sensors, a type of resistive sensor [ 16 ], primarily detect resistance changes due to mechanical stretching [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Silver Nanowire-Based Flexible Strain Sensor for Human Motion Detection

Mijit,

Li,

Wang

et al. 2024

Sensors

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Accurately capturing human movements is a crucial element of health status monitoring and a necessary precondition for realizing future virtual reality/augmented reality applications. Flexible motion sensors with exceptional sensitivity are capable of detecting physical activities by converting them into resistance fluctuations. Silver nanowires (AgNWs) have become a preferred choice for the development of various types of sensors due to their outstanding electrical conductivity, transparency, and flexibility within polymer composites. Herein, we present the design and fabrication of a flexible strain sensor based on silver nanowires. Suitable substrate materials were selected, and the sensor’s sensitivity and fatigue properties were characterized and tested, with the sensor maintaining reliability after 5000 deformation cycles. Different sensors were prepared by controlling the concentration of silver nanowires to achieve the collection of motion signals from various parts of the human body. Additionally, we explored potential applications of these sensors in fields such as health monitoring and virtual reality. In summary, this work integrated the acquisition of different human motion signals, demonstrating great potential for future multifunctional wearable electronic devices.

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“…In the field of rehabilitation, EMS has been utilized to treat impaired muscle contraction caused by neuromuscular injuries. Various force response models [ 27 , 28 , 29 , 30 ] with sensors to measure level of muscle contraction, such as electromyography (EMG) [ 31 , 32 ], mechanomyography (MMG) [ 33 , 34 ], and piezoresistive sensors [ 35 , 36 , 37 , 38 , 39 ], have been proposed to precisely control the contraction of impaired muscles in EMS-based rehabilitation. Although these models can represent the nonlinear features of the force response with respect to the various parameters of an electrical stimulation, it remains difficult to apply these models to haptic applications because of the discrepancy of target muscles.…”

Section: Introductionmentioning

confidence: 99%

Electrically Elicited Force Response Characteristics of Forearm Extensor Muscles for Electrical Muscle Stimulation-Based Haptic Rendering

Lee

Kim

Jung

2020

Sensors

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A haptic interface based on electrical muscle stimulation (EMS) has huge potential in terms of usability and applicability compared with conventional haptic interfaces. This study analyzed the force response characteristics of forearm extensor muscles for EMS-based haptic rendering. We introduced a simplified mathematical model of the force response, which has been developed in the field of rehabilitation, and experimentally validated its feasibility for haptic applications. Two important features of the force response, namely the peak force and response time, with respect to the frequency and amplitude of the electrical stimulation were identified by investigating the experimental force response of the forearm extensor muscles. An exponential function was proposed to estimate the peak force with respect to the frequency and amplitude, and it was verified by comparing with the measured peak force. The response time characteristics were also examined with respect to the frequency and amplitude. A frequency-dependent tendency, i.e., an increase in response time with increasing frequency, was observed, whereas there was no correlation with the amplitude. The analysis of the force response characteristics with the application of the proposed force response model may help enhance the fidelity of EMS-based haptic rendering.

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The Piezo-resistive MC Sensor is a Fast and Accurate Sensor for the Measurement of Mechanical Muscle Activity

Cited by 10 publications

References 38 publications

Surface‐Level Muscle Deformation as a Correlate for Joint Torque

Surface‐Level Muscle Deformation as a Correlate for Joint Torque

Silver Nanowire-Based Flexible Strain Sensor for Human Motion Detection

Electrically Elicited Force Response Characteristics of Forearm Extensor Muscles for Electrical Muscle Stimulation-Based Haptic Rendering

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