An Embedded Sensing and Communication Platform, and a Healthcare Model for Remote Monitoring of Chronic Diseases

Abstract

This paper presents a new remote healthcare model, which, exploiting wireless biomedical sensors, an embedded local unit (gateway) for sensor data acquisition-processing-communication, and a remote e-Health service center, can be scaled in different telemedicine scenarios. The aim is avoiding hospitalization cost and long waiting lists for patients affected by chronic illness who need continuous and long-term monitoring of some vital parameters. In the "1:1" scenario, the patient has a set of biomedical sensors and a gateway to exchange data and healthcare protocols with the remote service center. In the "1:N" scenario the use of gateway and sensors is managed by a professional caregiver, e.g., assigned by the Public Health System to a number N of different patients. In the "point of care" scenario the patient, instead of being hospitalized, can take the needed measurements at a specific health corner, which is then connected to the remote e-Health center. A mix of commercially available sensors and new custom-designed ones is presented. The new custom-designed sensors range from a single-lead electrocardiograph for easy measurements taken by the patients at their home, to a multi-channel biomedical integrated circuit for acquisition of multi-channel bio signals, to a new motion sensor for patient posture estimation and fall detection. Experimental trials in real-world telemedicine applications assess the proposed system in terms of easy usability from patients, specialist and family doctors, and caregivers, in terms of scalability in different scenarios, and in terms of suitability for implementation of needed care plans.

Recent Advances on Wearable Electronics and Embedded Computing Systems for Biomedical Applications

“…In the frame of wearable electronics and embedded computing systems for biomedical applications, this Special Issue of Electronics includes a total of 14 papers, including two review papers and twelve research articles [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. The issue spans a wide range of topics, including smart sensing footwear systems, human-body hydration monitoring, textile-based ECG monitoring in human and horses, biotelemetry and telemedicine, support for surgical navigation, wearable autonomic nervous system activity monitoring, and hand posture and tactile pressure sensing [2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

“…The issue spans a wide range of topics, including smart sensing footwear systems, human-body hydration monitoring, textile-based ECG monitoring in human and horses, biotelemetry and telemedicine, support for surgical navigation, wearable autonomic nervous system activity monitoring, and hand posture and tactile pressure sensing [2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

“…The authors conclude that the frequency of the external electrical source affects the accuracy of arousal recognition. Saponara et al [15] present a scalable remote model for telemedicine scenarios using wireless biomedical sensors, an embedded local unit (gateway) for sensor data acquisition/processing/communication, and a remote e-Health service center. The use of a mix of commercially available sensors and new custom-designed ones was also presented.…”

Fully-Integrated Converter for Low-Cost and Low-Size Power Supply in Internet-of-Things Applications

“…These "things" can be part of complex systems for healthcare [18][19][20][21][22][23][24][25], smart agriculture [26], science experiments [27], vehicles [28][29][30][31][32], satellites [33][34][35], domotics [36,37], robots/drones or industrial machines [38][39][40], telecom or surveillance apparatus [41][42][43], sport [44,45] or energy/smart-grid systems [46][47][48][49][50], and/or consumer electronics [51][52][53][54][55][56][57]. These units are usually wireless nodes, working at sub-GHz frequencies or in the range 2.4 GHz to 6 GHz [58][59][60][61], or at mm-waves [62][63][64].…”

An Open Platform for Seamless Sensor Support in Healthcare for the Internet of Things

“…Saponara et al [33] presented a Remote Healthcare Model and Embedded Sensing/ Communication platform to support multiple chronic illnesses. The authors developed and tested the platform with three healthcare scenarios in mind: self-measurement by the patient (1:1), measurement made by a professional caregiver (1:N) and measurement by the patient on a specific healthcare facility (point-of-care).…”