technology scaling enables today the design of ultra-low power wearable biosensors for continuous vital signal monitoring or wellness applications. Wireless Body sensor Networks (WBSN) integrate wearable sensing nodes...
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ISBN:
(纸本)9781467392280
technology scaling enables today the design of ultra-low power wearable biosensors for continuous vital signal monitoring or wellness applications. Wireless Body sensor Networks (WBSN) integrate wearable sensing nodes for an accurate measurement of the desired physiological parameter, e.g. Electrocardiogram (ECG), and a personal gateway for the collection and processing of the data. The diffusion of smartphones enables their use as advanced personal gateways, with the ability to provide user interaction features, connectivity and real-time feedback to the user. Both the sensing node(s) and the smartphone are battery powered and resource-constrained devices, hence energy efficiency is one of the key design goals. In this work, we explore the use of compression techniques to improve the efficiency of a wireless ECG wearable monitor. In the presented system, the wearable node is used for bio-signal acquisition, pre-processing and compression, while a smartphone is used for real-time signal reconstruction. The system aims at medical-grade signal quality and the impact of lossy compression is tested on real signals acquired by the node and its effects are evaluated on systemlevel energy consumption. We analyze performance/energy tradeoffs considering online data compression on the wearable device and real-time reconstruction on the smartphone. Our results show that Compressed Sensing pays off only when the SNR requirement is below 20 dB due to the non-ideal sparsity of ECG signal. We propose a hybrid compression scheme based on CS and under-quantization to address these limitations.
A potential approach to improve firefighters' performance in difficult emergencies has been the combination of exoskeletons with Internet of Things (IoT) technologies in recent years. To provide adaptive assistanc...
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ISBN:
(数字)9798331540661
ISBN:
(纸本)9798331540678
A potential approach to improve firefighters' performance in difficult emergencies has been the combination of exoskeletons with Internet of Things (IoT) technologies in recent years. To provide adaptive assistance to firefighters during crucial missions, this research presents a new framework that uses reinforcement learning (RL) algorithms combined with IoT exoskeletons. The proposed system uses interconnected sensors built into the exoskeletons to track various environmental and physiological variables, including core temperature, heart rate, and ambient light intensity. Firefighters' health and the danger level of the environment are evaluated using these data points in real time. Autonomously adjusting their support systems to offer appropriate help based on the dynamic situation, the exoskeletons use RL techniques. The system learns to predict the actions of firefighters, adapt the amount of help in real-time, and maximize energy efficiency to keep running for longer due to feedback and iterative learning processes. Firefighters and incident command centers can communicate seamlessly with the proposed framework, allowing real-time situational awareness and decision assistance. Firefighters' ability to be safe and successful during emergency operations is greatly enhanced by exoskeletons. smart solutions can protect first responders from harm and make them more resilient in dangerous situations.
With the aging population problem getting more and more aggravated, the number of hemiplegia patients increases rapidly, which results in the increasing requirement of rehabilitation training for regaining the body mo...
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ISBN:
(纸本)9781509027347
With the aging population problem getting more and more aggravated, the number of hemiplegia patients increases rapidly, which results in the increasing requirement of rehabilitation training for regaining the body movement function. Taking advantages of rehabilitation robots makes the rehabilitation training more scientific and efficient compared to traditional rehabilitation measures such as manual training. By now, many types of rehabilitation robots have been proposed by researchers. However, from the view of the physiological structure, many of them can't well fit the motion characteristics. Ankle plays an important role in standing, walking and so on. As the motion of these robots is different from the motion characteristics of ankles, it would make an undesired influence on the training effect. Rehabilitation robots have many structures, and they are mainly serial mechanism and parallel mechanism. However, serial mechanism is inconvenient to package. In this paper, a new type of parallel mechanism with five degrees of freedom was proposed. Compared to serial mechanism, parallel mechanism is convenient to package and it has larger motion area. It enables ankles to rotate around the rotary center of the ankle. With the screw theory, the degree of freedom was calculated. To verify the working space of the mechanism, the working space simulation was carried out by Matlab. Finally, the quantity and position of motors are determined.
Personal Robots and Robot technology (RT)-based assistive devices are expected to play a major role in Japan's elderly-dominated society, both for joint activities with their human partners and for participation i...
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ISBN:
(纸本)9781424412631;1424412633
Personal Robots and Robot technology (RT)-based assistive devices are expected to play a major role in Japan's elderly-dominated society, both for joint activities with their human partners and for participation in community life. These new devices should be capable of smooth and natural adaptation and interaction with their human partners and the environment, should be able to communicate naturally with humans, and should never have a negative effect on their human partners, neither physical nor emotional. To achieve this smooth and natural integration between humans and robots, we need first to investigate and clarify how these interactions are carried out. Therefore, we developed the portable Bioinstrumentation System WB-1R (Waseda Bioinstrumentation system no.1 Refined), which can measure the movements of the head, the arms, the hands (position, velocity, and acceleration), as well as several physiological parameters (electrocardiogram, respiration, perspiration, pulse wave, and so on), to objectively measure and understand the physical and physiological effects of the interaction between robots and humans. In this paper we present our development of the head and hands motion capture systems as additional modules for the Waseda Bioinstrumentation system No.1 (WB-1). The preliminary experimental results, given the inexpensiveness of the systems, are good for our purposes.
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