30,741 research outputs found
On-body device localization for health and medical monitoring applications
Abstract—We present a technique to discover the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it pro-vides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the user’s body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89 % accuracy in estimating the location of devices on the body. Keywords-On-body device localization, Unsupervised activity discovery, Motion analysis I
RFID Localisation For Internet Of Things Smart Homes: A Survey
The Internet of Things (IoT) enables numerous business opportunities in
fields as diverse as e-health, smart cities, smart homes, among many others.
The IoT incorporates multiple long-range, short-range, and personal area
wireless networks and technologies into the designs of IoT applications.
Localisation in indoor positioning systems plays an important role in the IoT.
Location Based IoT applications range from tracking objects and people in
real-time, assets management, agriculture, assisted monitoring technologies for
healthcare, and smart homes, to name a few. Radio Frequency based systems for
indoor positioning such as Radio Frequency Identification (RFID) is a key
enabler technology for the IoT due to its costeffective, high readability
rates, automatic identification and, importantly, its energy efficiency
characteristic. This paper reviews the state-of-the-art RFID technologies in
IoT Smart Homes applications. It presents several comparable studies of RFID
based projects in smart homes and discusses the applications, techniques,
algorithms, and challenges of adopting RFID technologies in IoT smart home
systems.Comment: 18 pages, 2 figures, 3 table
Distance Aware Relaying Energy-efficient: DARE to Monitor Patients in Multi-hop Body Area Sensor Networks
In recent years, interests in the applications of Wireless Body Area Sensor
Network (WBASN) is noticeably developed. WBASN is playing a significant role to
get the real time and precise data with reduced level of energy consumption. It
comprises of tiny, lightweight and energy restricted sensors, placed in/on the
human body, to monitor any ambiguity in body organs and measure various
biomedical parameters. In this study, a protocol named Distance Aware Relaying
Energy-efficient (DARE) to monitor patients in multi-hop Body Area Sensor
Networks (BASNs) is proposed. The protocol operates by investigating the ward
of a hospital comprising of eight patients, under different topologies by
positioning the sink at different locations or making it static or mobile.
Seven sensors are attached to each patient, measuring different parameters of
Electrocardiogram (ECG), pulse rate, heart rate, temperature level, glucose
level, toxins level and motion. To reduce the energy consumption, these sensors
communicate with the sink via an on-body relay, affixed on the chest of each
patient. The body relay possesses higher energy resources as compared to the
body sensors as, they perform aggregation and relaying of data to the sink
node. A comparison is also conducted conducted with another protocol of BAN
named, Mobility-supporting Adaptive Threshold-based Thermal-aware
Energy-efficient Multi-hop ProTocol (M-ATTEMPT). The simulation results show
that, the proposed protocol achieves increased network lifetime and efficiently
reduces the energy consumption, in relative to M-ATTEMPT protocol.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
Wireless Health Monitoring using Passive WiFi Sensing
This paper presents a two-dimensional phase extraction system using passive
WiFi sensing to monitor three basic elderly care activities including breathing
rate, essential tremor and falls. Specifically, a WiFi signal is acquired
through two channels where the first channel is the reference one, whereas the
other signal is acquired by a passive receiver after reflection from the human
target. Using signal processing of cross-ambiguity function, various features
in the signal are extracted. The entire implementations are performed using
software defined radios having directional antennas. We report the accuracy of
our system in different conditions and environments and show that breathing
rate can be measured with an accuracy of 87% when there are no obstacles. We
also show a 98% accuracy in detecting falls and 93% accuracy in classifying
tremor. The results indicate that passive WiFi systems show great promise in
replacing typical invasive health devices as standard tools for health care.Comment: 6 pages, 8 figures, conference pape
Breathfinding: A Wireless Network that Monitors and Locates Breathing in a Home
This paper explores using RSS measurements on many links in a wireless
network to estimate the breathing rate of a person, and the location where the
breathing is occurring, in a home, while the person is sitting, laying down,
standing, or sleeping. The main challenge in breathing rate estimation is that
"motion interference", i.e., movements other than a person's breathing,
generally cause larger changes in RSS than inhalation and exhalation. We
develop a method to estimate breathing rate despite motion interference, and
demonstrate its performance during multiple short (3-7 minute) tests and during
a longer 66 minute test. Further, for the same experiments, we show the
location of the breathing person can be estimated, to within about 2 m average
error in a 56 square meter apartment. Being able to locate a breathing person
who is not otherwise moving, without calibration, is important for applications
in search and rescue, health care, and security
Heart Failure Monitoring System Based on Wearable and Information Technologies
In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilitie
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