A remote patient health monitoring system that can be installed at homes or hospitals promises to spare healthcare workers the risk of exposure to COVID-19 while attending to persons undergoing isolation either for suspected infection or as precautionary quarantine.
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Jointly developed by Bharat Electronics Ltd. and the All India Institute of Medical Sciences (AIIMS) Rishikesh, the system reduces the need for scarce personal protective gear.
“The solution aims to significantly reduce the risk of exposure to healthcare workers,” BEL said in a statement on Thursday. “It is also expected to reduce the increasing demand of PPE [personal protective equipment] and logistics,” the public sector company added.
The system will also help to generate hot spots so that authorities can contain these zones.
The device has non-invasive sensors to measure the main parameters of a person who may be a COVID-19 patient: temperature, pulse rate, SPO2 or saturated oxygen level, and respiration rate.
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BEL said it developed a proof of concept model of the system based on inputs given by AIIMS - Rishikesh. The public enterprise used its expertise in network centric and IoT (Internet of things) systems.
How it works
A mobile app and Web browser have been developed. People who show symptoms of infection get enrolled with AIIMS - Rishikesh. The hospital will assess their complaints and if found necessary, will provide these individuals with a kit to help monitor their health parameters regularly.
“Patient health parameters, along with patient location, are uploaded on a regular basis on to a centralised command & control centre (CCC) on cloud using either the patient’s mobile phone or integral GSM SIM card,” BEL said. “The use of cloud will facilitate seamless scaling of the database of COVID-19 suspects/patients,” it added.
When the monitored parameters exceed preset thresholds, the software would send out alert messages to the medical officers and healthcare workers. It would also show the severity of the patient’s condition in different colour codes.
The geographical distribution of suspected or infected cases could also be obtained using the system’s data analytics software.
