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  • Researchers Design System to Help Elderly During Falls

    By NE Reporter on August 14, 2019

    SYDNEY:
    Drones, smartphones and sensors can provide relief to the elderly who are at risk of falls as researchers, including one of an Indian origin, have designed a new system to remotely monitor the elderly and provide quick first-aid when needed.

    The system detects abnormalities in the elderly”s heart rate and temperature and also provides urgent first aid via drones if a fall occurs. In the study published in the journal Sensors, the researchers describe how a wearable device can monitor vital signs using a wireless sensor attached to the upper arm and send a message to an emergency call centre if physiological abnormalities or a fall are detected.

    “When a case is critical, first aid supplies can be delivered to the patient via a drone, up to 105 seconds faster than an ambulance,” said Indian-origin researcher Javaan Chahl, Professor at the South Australia University. “We have also designed an advanced smartphone-based program that uses an intelligent autopilot, containing a destination waypoint for planning the path of a drone,” said Sadik Kamel Gharghan from Middle Technical University in Iraq.

    The fall detection device consists of a micro-controller, two bio-sensors, a GPS module to track the location and a GSM module to send a notification to the smartphones of caregivers. The second part includes a first aid package, a smartphone and a drone to deliver the package.

    It is estimated that around 30 per cent of adults over the age of 65 experience at least one fall a year, in many cases fracturing a hip, or sustaining head injuries. The annual global cost of fall-related acute care for older people has risen dramatically in recent years as the world”s population ages.

    The most recent figures show that falls account for 40 per cent of injury-related deaths and one per cent of total deaths in people aged over 65 years.

     

    NE Reporter

    DronesFallsfirst aidphysiological abnormalitiessensorssmartphonesWearable Device

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