A medical tele-tutoring system for the Emergency Service

Ruscelli, Anna Lina; Cecchetti, Gabriele; Barsanti, Igor; Manciulli, Mirco; Paolini, Piero; Castoldi, P.

doi:10.1109/percomworkshops51409.2021.9431030

Cited by 5 publications

(1 citation statement)

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“…Telemedicine applications have begun assisting ambulance crews because the emergency services deploy rapid response teams consisting of nurses and volunteers, but not doctors. By using a Raspberry Pi and a commercially available webcam, the wearable solution of medical tele-tutoring REC-VISIO 118 can provide a stabilized video of the situation, mainly for first aid interventions, that can be accessed through a web interface in real-time through a 4G connection, leading to a faster pre-diagnosis for time-dependent conditions such as heart attacks or strokes [ 46 ].…”

Section: Overview Of Healthcare Applicationsmentioning

confidence: 99%

A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence

Pap

Oniga

2022

IJERPH

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Over the last couple of years, in the context of the COVID-19 pandemic, many healthcare issues have been exacerbated, highlighting the paramount need to provide both reliable and affordable health services to remote locations by using the latest technologies such as video conferencing, data management, the secure transfer of patient information, and efficient data analysis tools such as machine learning algorithms. In the constant struggle to offer healthcare to everyone, many modern technologies find applicability in eHealth, mHealth, telehealth or telemedicine. Through this paper, we attempt to render an overview of what different technologies are used in certain healthcare applications, ranging from remote patient monitoring in the field of cardio-oncology to analyzing EEG signals through machine learning for the prediction of seizures, focusing on the role of artificial intelligence in eHealth.

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Section: Overview Of Healthcare Applicationsmentioning

confidence: 99%