HeartCycle: Advanced sensors for telehealth applications

Luprano, Jean; Carvalho, Paulo; Eilebrecht, Benjamin; Kortelainen, Juha; Muehlsteff, Jens; Sipila, Auli; Solà, Josep; Teichmann, Daniel; Ulbrich, Mark

doi:10.1109/embc.2013.6611165

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…Several research groups and industry have initiated projects in the AAL area, for instance My-Heart [25], an EU FP6 project with Philips Research group focusing on vital sign monitoring to save lives by providing earlier diagnoses, closer monitoring and a means to help people manage any heart problems. In addition, HeartCycle project [11,24], also coordinated by Philips, provide a closed-loop disease management solution being able to serve both Heart Failure (HF) patients and Coronary Heart Disease (CHD) patients, including possible co-morbidities hypertension, diabetes and arrhythmias. This has been achieved by multi-parametric monitoring and analysis of vital signs and other measurements.…”

Section: State-of-the-artmentioning

confidence: 99%

Remote health monitoring of elderly through wearable sensors

Al-Khafajiy¹,

Baker²,

Chalmers³

et al. 2019

Multimed Tools Appl

277

103

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Due to a rapidly increasing aging population and its associated challenges in health and social care, Ambient Assistive Living has become the focal point for both researchers and industry alike. The need to manage or even reduce healthcare costs while improving the quality of service is high government agendas. Although, technology has a major role to play in achieving these aspirations, any solution must be designed, implemented and validated using appropriate domain knowledge. In order to overcome these challenges, the remote real-time monitoring of a person's health can be used to identify relapses in conditions, therefore, enabling early intervention. Thus, the development of a smart healthcare monitoring system, which is capable of observing elderly people remotely, is the focus of the research presented in this paper. The technology outlined in this paper focuses on the ability to track a person's physiological data to detect specific disorders which can aid in Early Intervention Practices. This is achieved by accurately processing and analysing the acquired sensory data while transmitting the detection of a disorder to an appropriate career. The finding reveals that the proposed system can improve clinical decision supports while facilitating Early Intervention Practices. Our extensive simulation results indicate a superior performance of the proposed system: low latency (96% of the packets are received with less than 1 millisecond) and low packets-lost (only 2.2% of total packets are dropped). Thus, the system runs efficiently and is cost-effective in terms of data acquisition and manipulation.

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Section: State-of-the-artmentioning

confidence: 99%

Remote health monitoring of elderly through wearable sensors

Al-Khafajiy¹,

Baker²,

Chalmers³

et al. 2019

Multimed Tools Appl

277

103

View full text Add to dashboard Cite

show abstract

“…To obtain high quality ECGs, advanced ECG devices are equipped with shielding and signal conditioning circuits [14], gel-free electrodes, contactless electrodes (garments with embedded electrodes) [15], or other sensors (e.g., a 3D accelerometer to measure the patient's motion, and use this feedback to cancel out motion artifacts). Different from traditional conductive ECG devices that use electrodes, the latest capacitive ECG devices utilize the capacitive coupling principle to obtain ECG signals, which eliminates the electrochemical half-cell potential that may vary with ion concentrations on the skin.…”

Section: Sensors For Ecg Icg and Ppgmentioning

confidence: 99%

On Sensor Technologies in CVD Diagnosis

Du¹

2015

IJMMM

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Abstract-Major applications of sensor technologies in cardiovascular disease (CVD) diagnoses include (1) detect heart pulse waveforms, (2) measure blood properties, (3) create heart or vessel images, and (4) establish wireless CVD detecting or monitoring network. Sensors such as piezoresistive and strain gauge sensors have been used to automatize or modernize TCPD; conductive, impedance, and optical sensors have been utilized to obtain ECG, ICG, and PPG waveforms, respectively, to assess the patient's cardiovascular status; piezoelectric sensors are used in ultrasound devices to generate a moving picture of the heart, show its size, shape, structure, and how well its valves are working; piezoelectric sensors, as well as electromagnetic and capacitive sensors can also be used to detect and record the sounds from the heart or blood flow in arteries and veins. Radiation sensors detect penetrated X-ray to create CCT images; inductive sensors (coils) can pick up 10-100MHz radio waves released from soft tissues after their H-atoms' magnetic resonance and create a cardiac MRI.

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