Energy saving mechanism for a Smart Wearable System: monitoring infants during the sleep

In Smart Wearable Systems (SWS), the wearable devices are powered by batteries with very limited energy available. These emergent systems have strong Quality of Service (QoS) requirements, with focus on reliable communication and low power consumption. This is the scope of the Baby Night Watch, a project developed in the context of the European Texas Instruments Innovation Challenge (TIIC) 2015. This Project consists of a monitoring tool for infants, which matches different emergent research fields. SWSs require energy saving mechanism to reduce the energy wasting during wireless communications. A Transmission Power Control (TPC) mechanism that changes its characteristics according to the scenario of operation, is proposed. It uses sensors to determine the position of the infant and, based on that, predicts the current state of the channel. Other TPC algorithms are implemented and their performance are compared with our novel mechanism. The proposed TPC mechanism outperforms the existing ones in terms of the energy saving.Duarte Fernandes and André G. Ferreira are supported by FCT (grant SFRH/BD/92082/2012 and SFRH/BD/91477/2012 respectively). This work was partially funded by FCT within the Project Scope: Pest-OE/EEI/UI0319/2014, and partially funded by -Programa Operacional Factores de Competitividade – COMPETE and National funds through FCT – Fundação para a Ciência e a Tecnologia- under the project UID/CTM/00264

On-Body Channel Measurement Using Wireless Sensors

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A synergistic wearable health monitoring system using cellular network technology

Thesis (M.S.) University of Alaska Fairbanks, 2017This thesis presents a synergistic approach to healthcare applications by integrating a wearable health monitoring system into a smart home system. By exploiting synergy within each system and between these two systems, this thesis shows that the efficiency of the health care can be increased while providing the added advantage of utmost user-friendly environment. Initially, a wearable health monitoring prototype system was developed for vital sign data collection and processing. The developed system used biosensor integration to distinguish amongst multiple physical activities and to compare the variations in physiological conditions according to physical activity of the user. Afterward, system learning techniques were established for accomplishing the scalability of the health monitoring system. The resulting system is able to monitor different users without the need for explicitly changing the thresholds for the individual user. The health monitoring was further improved through integration with the smart home system to exploit synergy between various physiological sensors and to reduce false alarms generated by the system. A cellular communication interface was developed for transmitting the collected data to a remote caregiver and also to store the time-stamped data on the online web server. A web interface was developed to allow monitoring user's health and activity data, along with their surrounding environment

Body-centric Wireless Hospital Patient Monitoring Networks using Body-contoured Flexible Antennas

This paper presents empirical results from a measurement campaign to investigate futuristic body-centric medical mesh networks for a hospitalized patient using flexible body-contouring antennas. It studies path loss in a medical environment (in a hospital bed in an open hospital ward) for UWB and four narrowband schemes concurrently. It firstly investigates the antenna contouring effects due to mounting the flexible antennas on various body surfaces, then uses statistical analysis to explore optimal body locations for a master node to inform allocation of processing power (assuming point-to-point link from other nodes). Results indicated how the most suitable body location varies depending on the posture and frequency scheme used. Also investigated are best route selections for multi-hop mesh network topologies for opportunistic networking for each of the presented postures and frequencies; this reveals how less hops were required to navigate around the narrowband network compared to UWB which effectively reduces required processing power and data traffic. Understanding how disparate body-centric medical devices communicate with one another in a body-mesh network is instrumental to the strategic and informed development of next generation healthcare patient monitoring solutions

Wearables for independent living in older adults: Gait and falls

Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) is one approach that offers a viable means for ubiquitous, sustainable and scalable monitoring of the health of older adults in habitual free-living environments. Gait has been presented as a relevant (bio)marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research-grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic, with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of the recent literature on gait assessment through the use of wearables, focusing on the need for an algorithm fusion approach to measurement, culminating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Suggestions for how this domain needs to progress are also summarised