Wireless Wearable Magnetometer-Based Sensor for Sleep Quality Monitoring

Milici, Stefano; Lázaro, Antonio; Villarino, R.; Girbau, David; Magnarosa, Marco

doi:10.1109/jsen.2018.2791400

Cited by 81 publications

(50 citation statements)

References 29 publications

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“…Nowadays, one of the key and most relevant applications of wearables is in localization systems [7][8][9]. In fact, wearables can now include, for instance: (i) inertial sensors for measuring the angular velocity and linear acceleration [10]; (ii) magnetometer for measuring the heading [11]; and (iii) proximity sensors for detecting if a defined subject or obstacle is present nearby [12].…”

Section: Introductionmentioning

confidence: 99%

Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

et al. 2019

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Over the years, several Ultrawideband (UWB) localization systems have been proposed and evaluated for accurate estimation of the position for pedestrians. However, most of them are evaluated for a particular wearable sensor position; hence, the accuracy obtained is subject to a given wearable sensor position. This paper is focused on studying the effects of body wearable sensor positions i.e., chest, arm, ankle, wrist, thigh, forehead, and hand, on the localization accuracy. According to our results, the forehead and the chest provide the best and worst body sensor location for tracking a pedestrian, respectively. With the wearable sensor at the forehead and chest position, errors lower than 0.35 m (90th percentile) and 4 m can be obtained, respectively. The reason for such a contrast in the performance lies in the fact that, in non-line-of-sight (NLOS) situations, the chest generates the highest multipath of any part of the human body. Thus, the large errors obtained arise due to the signal arriving at the target wearable sensor by multiple reflections from interacting objects in the environment rather than by direct line-of-sight (LOS) or creeping wave propagation mechanism.

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Section: Introductionmentioning

confidence: 99%

Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

et al. 2019

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“…Furthermore, movements from breathing activities can be detected by measuring the magnetic field strength around the chest area using a magnetometer. The magnetic field variation can be measured by either simply placing a magnetometer on the chest of the subject using a belt [87] or placing a magnet and a magnetometer on the back and chest area of the subject, respectively [88]. Nevertheless, the use of a magnet enables lower power consumption.…”

Section: Chest-wall Displacement Sensingmentioning

confidence: 99%

Human Vital Signs Detection Methods and Potential Using Radars: A Review

Kebe

Gadhafi

Mohammad

et al. 2020

Sensors

135

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Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject’s body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.

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“…However, other technologies can be used, such as super-capacitors, which can now achieve energy density levels that are comparable to lead-acid batteries. In addition, super-capacitors are environmentally friendly and offer high power density, fast charging/discharging speed, and a long lifecycle [112]. The requirements of batteries change significantly depending on the wearable energy consumption.…”

Section: Challengesmentioning

confidence: 99%

Energy Harvesting Techniques for Wireless Sensor Networks/Radio-Frequency Identification: A Review

2019

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In the near future, symmetry technologies for the Internet of Things (IoT), along with symmetry and asymmetry applications for IoT security and privacy, will re-design the socio-ecological human terrain morphology. The IoT ecosystem deploys diverse sensor platforms connecting billions of heterogeneous objects through the Internet. Most sensors are low-energy consuming devices which are designed to transmit sporadically or continuously. However, when we consider the billions/trillions of connected sensors powering various user applications, their energy efficiency (EE) becomes a critical issue. Therefore, the importance of EE in IoT technology cannot be overemphasised, specifically the development of EE solutions for sustainable IoT technology. Propelled by this need, EE proposals are expected to address IoT’s EE issues. Consequently, many developments have been displayed, and highlighting them to provide clear insights into eco-sustainable and green IoT technologies is becoming a crucial task. To pursue a clear vision of green IoT, this article aims to describe the current state-of-the art insights into energy-saving practices and strategies on green IoT. The major contribution of this study is the review and discussion of the substantial issues enabling hardware green IoT to focus on green wireless sensor networks and green radio-frequency identification. This review paper will contribute significantly to the future implementation of green and eco-sustainable IoT.

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Wireless Wearable Magnetometer-Based Sensor for Sleep Quality Monitoring

Cited by 81 publications

References 29 publications

Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

Human Vital Signs Detection Methods and Potential Using Radars: A Review

Energy Harvesting Techniques for Wireless Sensor Networks/Radio-Frequency Identification: A Review

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