ATTICUS: Ambient-Intelligent Tele-monitoring and Telemetry for Incepting and Catering Over hUman Sustainability

Abstract

Wearable devices as medical technologies are becoming an integral part of our lives. Many research studies are dedicated to these devices and are mainly focused on providing personal analytics, measuring physical status, and acquiring physiological signals and parameters. These continuously evolving technologies play an important role in telemedicine. Telemedicine can be broadly defined as the use of advanced telecommunications technologies to support many medical activities, such as the diagnosis, the analysis of patient data, the improvement of disease management and the treatment in remote areas. In this article, we present ATTICUS (Ambient-intelligent Tele-monitoring and Telemetry for Incepting and Catering over hUman Sustainability), an innovative remote monitoring system for ambient-assisted living based on the analysis of vital and behavioral parameters. The ATTICUS system consists of two essential components: a smart wearable—in the form of a short singlet—made of innovative textile which allows the acquisition of real-time body signals, e.g., electrocardiogram (ECG), breathing wave, temperature, and a multi-level Decision Support System (DSS), a distributed software which integrates advanced machine learning methods to automatically detect anomalies. ATTICUS is capable of operating in different application scenarios. Especially, the system will support in-home and out-home monitoring, personal check-ups, and specialized check-ups. Thus, the system will positively impact the canonical medical practices allowing simultaneous and continuous monitoring of a large number of people.

ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals

“…The multi-lead proposed method implements a dynamic deterministic approach [26] in the sense that the compression mechanism is adapted to the acquired signals to include more information on cardiac features and improve reconstruction quality. The method is designed to be implemented in the Ambient-Intelligent Tele-monitoring and Telemetry for Incepting and Catering Over hUman Sustainability (ATTICUS) system described in [27]. This system consists of a smart T-shirt, called S-WEAR, capable of monitoring from one up to six ECG leads.…”

“…They allow automatic detection: atrial fibrillation, ventricular tachycardia, congestive heart failure, and four types of arrhythmia conditions. Some of these machine learning techniques work on multi-lead acquisitions for assuring high accuracy [27]. If an alarm is sent to the physician, long recordings of the acquired multi-lead signals before and after the detected event are sent to her/him in order to make a diagnosis.…”