One-Handed Wearable sEMG Sensor for Myoelectric Control of Prosthetic Hands

Jiang, Yinlai; Sakoda, Shintaro; Togane, Masami; Morishita, Soichiro; Yokoi, Hiroshi

doi:10.1007/978-981-10-2404-7_9

Cited by 4 publications

(7 citation statements)

References 8 publications

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“…For instance, wearable devices integrated with electromyography (EMG), inertial measurement units (IMU) and barometric pressure sensors, have been able to read physiological and biomechanical data in real-time (Asbeck et al, 2014;Massé et al, 2014). Recently, robotics has started to benefit from wearable devices in applications for search and rescue, assistive robotics, telemanipulation and telepresence (Martinez-Hernandez et al, 2017a;Jiang et al, 2017;Powell et al, 2016). Despite this progress, the design of fast and accurate machine learning methods, needed to exploit the potential of wearable technologies for recognition of human activities, are still under development.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Martinez-Hernandez

Dehghani-Sanij

2019

Pattern Recognition Letters

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Identification of human movements is crucial for the design of intelligent devices capable to provide assistance. In this work, a Bayesian formulation, together with a sequential analysis method, is presented for identification of sit-to-stand (SiSt) and stand-to-sit (StSi) activities. This method performs autonomous iterative accumulation of sensor measurements and decision-making processes, while dealing with noise and uncertainty present in sensors. First, the Bayesian formulation is able to identify sit, transition and stand activity states. Second, the transition state, divided into transition phases, is used to identify the state of the human body during SiSt and StSi. These processes employ acceleration signals from an inertial measurement unit attached to the thigh of participants. Validation of our method with experiments in offline, real-time and a simulated environment, shows its capability to identify the human body during SiSt and StSi with an accuracy of 100% and mean response time of 50 ms (5 sensor measurements). In the simulated environment, our approach shows its potential to interact with low-level methods required for robot control. Overall, this work offers a robust framework for intelligent and autonomous systems, capable to recognise the human intent to rise from and sit on a chair, which is essential to provide accurate and fast assistance.

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Section: Introductionmentioning

confidence: 99%

Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Martinez-Hernandez

Dehghani-Sanij

2019

Pattern Recognition Letters

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“…Four articles did not specify the size of the electrodes, and three articles reported adjustable electrode size. 56,57,61 The orientation of the electrode with respect to the muscle fiber was poorly described in the reviewed literature, although the orientation is of importance.…”

Section: Electrode Configurationmentioning

confidence: 99%

“…Textiles as support materials -'add on' Mechanical attachment (often inorganic) Sleeves 38,39 Taping Socks 63 Temporary fixture (often for testing) Electrodes fixed by elastic band 59,65 Cut and sew Jogging 68,[72][73][74] Armband/sleeves/elastic band [47][48][49]56,57,61,64,67,70,76,77,79 Integrated onto Coating Knitted fabric straps 55 Stencil printing Armband/sleeves 58,60 Integrated into Embroidery/sewing Jogging Figure 6. Wearable system integration levels.…”

Section: System Integration Level Electrode (E) and Wearable System (mentioning

confidence: 99%

“…Prosthetic hand control. Powered prosthetic hands, 38,39,41,44,45,[47][48][49]56,57,60,61,65 which are controlled by myoelectric signals, are considerably more advanced than the control strategies used to command them. 24 The myoelectrical signal sensors commonly used for prosthetic hand control are large in size and stiff, which limit the number that can be applied to the limb and cause pressure-related discomfort for users.…”

Section: Reported Applicationsmentioning

confidence: 99%

“…Electrodes are tested as part of a system rather than as a single element. In total, 20 papers were categorized as focusing on system design, including 18 papers [40][41][42]44,45,49,56,57,61,63,67,71,73,76,77,79,82,83 on textile/wearable system design and two papers 64,68 on wearable acquisition system design, including an evaluation of the complete system.…”

Section: Various Types Of Reviewed Studiesmentioning

confidence: 99%

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Systematic review of textile-based electrodes for long-term and continuous surface electromyography recording

Guo

Sandsjö

Ortiz-Catalán

et al. 2019

Textile Research Journal

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This systematic review concerns the use of smart textiles enabled applications based on myoelectric activity. Electromyography (EMG) is the technique for recording and evaluating electric signals related to muscle activity (myoelectric). EMG is a well-established technique that provides a wealth of information for clinical diagnosis, monitoring, and treatment. Introducing sensor systems that allow for ubiquitous monitoring of health conditions using textile integrated solutions not only opens possibilities for ambulatory, long-term, and continuous health monitoring outside the hospital, but also for autonomous self-administration. Textile-based electrodes have demonstrated potential as a fully operational alternative to 'standard' Ag/AgCl electrodes for recording surface electromyography (sEMG) signals. As a substitute for Ag/AgCl electrodes fastened to the skin by taping or pre-gluing adhesive, textile-based electrodes have the advantages of being soft, flexible, and air permeable; thus, they have advantages in medicine and health monitoring, especially when selfadministration, real-time, and long-term monitoring is required. Such advances have been achieved through various smart textile techniques; for instance, adding functions in textiles, including fibers, yarns, and fabrics, and various methods for incorporating functionality into textiles, such as knitting, weaving, embroidery, and coating. In this work, we reviewed articles from a textile perspective to provide an overview of sEMG applications enabled by smart textile strategies. The overview is based on a literature evaluation of 41 articles published in both peer-reviewed journals and conference proceedings focusing on electrode materials, fabrication methods, construction, and sEMG applications. We introduce four textile integration levels to further describe the various textile electrode sEMG applications reported in the reviewed literature. We conclude with suggestions for future work along with recommendations for the reporting of essential benchmarking information in current and future textile electrode applications.

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Advances in Printed Electronic Textiles

Islam,

Afroj,

Yin

et al. 2023

Advanced Science

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Electronic textiles (e‐textiles) have emerged as a revolutionary solution for personalized healthcare, enabling the continuous collection and communication of diverse physiological parameters when seamlessly integrated with the human body. Among various methods employed to create wearable e‐textiles, printing offers unparalleled flexibility and comfort, seamlessly integrating wearables into garments. This has spurred growing research interest in printed e‐textiles, due to their vast design versatility, material options, fabrication techniques, and wide‐ranging applications. Here, a comprehensive overview of the crucial considerations in fabricating printed e‐textiles is provided, encompassing the selection of conductive materials and substrates, as well as the essential pre‐ and post‐treatments involved. Furthermore, the diverse printing techniques and the specific requirements are discussed, highlighting the advantages and limitations of each method. Additionally, the multitude of wearable applications made possible by printed e‐textiles is explored, such as their integration as various sensors, supercapacitors, and heated garments. Finally, a forward‐looking perspective is provided, discussing future prospects and emerging trends in the realm of printed wearable e‐textiles. As advancements in materials science, printing technologies, and design innovation continue to unfold, the transformative potential of printed e‐textiles in healthcare and beyond is poised to revolutionize the way wearable technology interacts and benefits.

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One-Handed Wearable sEMG Sensor for Myoelectric Control of Prosthetic Hands

Cited by 4 publications

References 8 publications

Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Systematic review of textile-based electrodes for long-term and continuous surface electromyography recording

Advances in Printed Electronic Textiles

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