Advanced observation and telemetry heart system utilizing wearable ECG device and a Cloud platform

Abstract

Short lived chest pain episodes of post PCI patients represent the most common clinical scenario treated in the Accidents and Emergency Room. Continuous ECG monitoring could substantially diminish such hospital admissions and related ambulance calls. Delivering community based, easy-to-handle, easy to wear, real time electrocardiography systems is still a quest, despite the existence of electronic electrocardiography systems for several decades. The PATRIOT system serves this challenge via a 12-channel, easy to wear, easy to carry, mobile linked, miniaturized automatic ECG device and a Cloud platform. The system may deliver high quality electrocardiograms of a patient to medical personnel either on the spot or remotely both in a synchronous or asynchronous mode, enhancing autonomy, mobility, quality of life and safety or recently treated coronary artery disease patients.

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

“…Of particular interest are systems that propose solutions to optimize processing and reduce the cost of data transmission and storage over the Cloud infrastructure [24,26,71,[143][144][145], this is also very crucial in cases of emergency and vital situations when real-time analytics are urgently required for actionable insights. Tuli et al [26] incorporated ensemble deep learning in edge computing devices and deployed it for the real-life application of automatic heart disease analysis.…”

Towards an Architecture to Guarantee Both Data Privacy and Utility in the First Phases of Digital Clinical Trials

“…Existing IoT devices targeting healthcare suffer from a lack of computational power to locally process the ECG recordings and detect abnormal behaviour. Therefore, recorded signals need to be transferred to cloud services where advanced analysis algorithms are executed for processing and integration [71,72]. In other trials, the freshness requirement can instead be relaxed.…”

Design and Evaluation of a Person-Centric Heart Monitoring System over Fog Computing Infrastructure

“…The design of efficient health monitoring systems has been a topic of active research over the last few years, mostly reinvigorated by the numerous advances in communication protocols and access technologies. Most researchers tried to merge wireless sensor networks with smart gateways [3,11], and also use smartphones as gateways for developing personal health monitoring systems [2,20]. Specialized diagnosis techniques are utilized for specific types of health monitoring applications [8] or platforms using dedicated IoT communication protocols [21], however, all aforementioned solutions somehow fail to harness the full extent of capabilities fog computing offers towards providing a holistic solution that will be applicable to a larger number of use cases, involving several actors.…”

“…This problem is addressed by introducing more than one recording points (three, six, twelve ECG leads) in order to acquire more information from more than one heart regions. The additional recording points increase the power consumption of the device and produce a high-definition signal that requires bigger memory capacity to be stored [2]. This creates a trade-off between accuracy and longevity of the wearable device.…”

“…Another critical aspect of existing wearable solutions is their lack of computational power to locally process the ECG recordings and detect abnormal behaviour. The recorded signal is transmitted to a nearby gateway device that relays the recording over to the cloud where advanced analysis algorithms are executed [2,10]. Depending on the number of leads used, even a trace of a short period can require large amounts of data to be transmitted over the wireless network, affecting the battery performance of the wearable device and possibly also that of the gateway (e.g., in case of a smartphone).…”