A self-powered wearable brain–machine-interface system for ceasing action

Wang, Xiang; Han, Yechao; Long, Zhihe; Zhang, Wanglinhan; Zhong, Tianyan; Liang, Shan; Xing, Lili; Xue, Xinyu; Zhan, Yang

doi:10.1039/d1nr08168c

Cited by 4 publications

(3 citation statements)

References 46 publications

(55 reference statements)

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“…Ultrahigh flexibility (Figure S2, Supporting Information) with a very fast response time (≈4 ms) (Figure S3, Supporting Information) enables FPS to detect even tiny muscular motions in the body (more information given in the Experimental Section). [ 35 ] The XRD technique is used to detect the piezoelectric phase in nylon‐11 (Figure S4a, Supporting Information), consists of a ferroelectric δ′ phase with crystallinity ≈38%. [ 36 ] Further confirmed by polarization versus electric field (P–E) measurement from the PE loop tracer (Premier II, Radiant Technologies), shows prominent ferroelectric properties [ 37 ] with remanent polarization ( P r ) of 0.2 µ C cm −2 (Figure S4b, Supporting Information).…”

Section: Resultsmentioning

confidence: 99%

Deep Learning Enabled Early Predicting Cardiovascular Status Using Highly Sensitive Piezoelectric Sensor of Solution‐Processable Nylon‐11

Babu¹,

Ranpariya

Sinha

et al. 2023

Adv Materials Technologies

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Cardiovascular diseases are found as one of the major cause of deaths globally, these can be reduced substantially if early‐stage detection and intervention is possible. Regular monitoring of the arterial pulse is one of the possible solutions, however, existing technologies have put limitations, due instability in continuous monitoring, lack of information in real‐time recording of cardiovascular parameters and bulky instruments. A highly sensitive flexible piezoelectric sensor of nylon‐11 fabricated is introduced from simple solution processable technique. Which consists of a highly sensitive, flexible, conformable piezoelectric film, owing to its high mechanosensitivity (≈225 mV N−1) in the subtle pressure range (0.001–1 kPa), and fast responsivity (≈4 ms), it is tested for assessing risk factors of cardiovascular diseases based on arterial pulse data. It is integrated with the internet of things (IoT) via system on a chip to facilitate remote healthcare monitoring. Deep learning algorithms is further interfaced with sensor for early detect and predict cardiovascular risks, showing an accuracy of >94% for predicting cardiovascular status. This piezoelectric sensor equipped with artificial intelligence and IoT has potential for monitoring the risk analysis of the cardiovascular diseases, daily activities, and facilitate to early predict the anomalous physiological changes in the body.

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Section: Resultsmentioning

confidence: 99%

Deep Learning Enabled Early Predicting Cardiovascular Status Using Highly Sensitive Piezoelectric Sensor of Solution‐Processable Nylon‐11

Babu¹,

Ranpariya

Sinha

et al. 2023

Adv Materials Technologies

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“…One of the reported cases is the RFID-inspired neurosensor considered for a wireless brain–machine interface, which is battery-less and the energy storage is accomplished using the concept of RF energy harvesting [ 44 ]. Similar research work is presented by Xiang et al in which authors have proposed and tested a self-powered brain machine that harvests energy from the movements of a human body part and sends a signal to the brain to cease some action [ 45 ]. Glucose sensors/meters are mostly referred to as amperometric sensors.…”

Section: Wban Technical Issuesmentioning

confidence: 96%

A Survey on Wireless Wearable Body Area Networks: A Perspective of Technology and Economy

Bhatti

Saleem

Imran

et al. 2022

Sensors

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The deployment of wearable or body-worn devices is increasing rapidly, and thus researchers’ interests mainly include technical and economical issues, such as networking, interoperability, security, power optimization, business growth and regulation. To address these issues properly, previous survey papers usually focused on describing the wireless body area network architecture and network protocols. This implies that deployment issues and awareness issues of wearable and BAN devices are not emphasized in previous work. To defeat this problem, in this study, we have focused on feasibility, limitations, and security concerns in wireless body area networks. In the aspect of the economy, we have focused on the compound annual growth rate of these devices in the global market, different regulations of wearable/wireless body area network devices in different regions and countries of the world and feasible research projects for wireless body area networks. In addition, this study focuses on the domain of devices that are equally important to physicians, sportsmen, trainers and coaches, computer scientists, engineers, and investors. The outcomes of this study relating to physicians, fitness trainers and coaches indicate that the use of these devices means they would be able to treat their clients in a more effective way. The study also converges the focus of businessmen on the Annual Growth Rate (CAGR) and provides manufacturers and vendors with information about different regulatory bodies that are monitoring and regulating WBAN devices. Therefore, by providing deployment issues in the aspects of technology and economy at the same time, we believe that this survey can serve as a preliminary material that will lead to more advancements and improvements in deployment in the area of wearable wireless body area networks. Finally, we present open issues and further research direction in the area of wireless body area networks.

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“…At the same time, some researchers have pointed out that brain electrical stimulation might be a good way to adjust body physiological parameters (such as body temperature, blood glucose concentration, and heartbeat rate). [16][17][18][19][20] For example, electrical stimulation on the median preoptic nucleus (MnPO) brain region can lower body temperature by inhibiting the body's heat production. [21][22][23][24][25][26] Thus, a wearable brain-machine-interface system that can detetct and adjust body temperature in real time has great potential applications in heat stroke treatment.…”

Section: Introductionmentioning

confidence: 99%

A self-powered wearable brain-machine-interface system for real-time monitoring and regulating body temperature

Zhong

Liang

et al. 2022

Nanoscale

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A self-powered wearable brain–machine-interface system for ceasing action

Abstract: A self-powered wearable brain-machine-interface system with pulse detection and brain stimulation for ceasing action has been realized. The system is composed of (1) a power supply unit that exploits piezoelectric...

Cited by 4 publications

References 46 publications

Deep Learning Enabled Early Predicting Cardiovascular Status Using Highly Sensitive Piezoelectric Sensor of Solution‐Processable Nylon‐11

Deep Learning Enabled Early Predicting Cardiovascular Status Using Highly Sensitive Piezoelectric Sensor of Solution‐Processable Nylon‐11

A Survey on Wireless Wearable Body Area Networks: A Perspective of Technology and Economy

A self-powered wearable brain-machine-interface system for real-time monitoring and regulating body temperature

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