Radar technology has emerged as a powerful tool in enhancing elderly care, providing innovative solutions for monitoring and ensuring the safety of senior citizens. By utilizing radar systems, caregivers can accurately track the movements and activities of elderly individuals without invasive measures. The non-contact and unobtrusive nature of radar technology also assists in location tracking for seniors with cognitive impairments, effectively reducing the risks associated with wandering, thus providing caregivers peace of mind.
Our mastery lies in the seamless integration of sensors into diverse applications, leading to enhanced data processes. Within the healthcare sector, our proficiency significantly improves data collection, analysis, and decision-making, specifically in the realms of image analysis and deep learning-based image segmentation technology.
Digital twin technology transforms the healthcare sector by enhancing the diagnosis and treatment of patients, optimizing preventive care, and enabling new strategies for hospital planning.
MulticoreWare offers engineering services through its Deep Learning Radar Technology, catering to a diverse range of features including:
Enhance the well-being of patients, especially the elderly through remote monitoring, telehealth services, wearable devices, and smart home technologies
Movement and Gait Analysis evaluate movement patterns, stride length, and posture for biomechanical assessment, injury prevention, and rehab.
Advanced Sleep Analysis involves the use of advanced technologies such as wearable devices, sensors, and data analytics to gather comprehensive information about an individual’s sleep cycle, quality, and various physiological parameters during sleep.
Track physiological parameters like heart rate, blood pressure, and oxygen levels; detect changes requiring medical attention with specialized devices.
Interpret medical imaging like X-Rays, CT scans, aiding efficient detection and diagnosis of medical conditions.
Deliver remote therapy via video conferencing, wearables, and personalized treatment plans.
It aims to deliver more relevant and personalized assistance to users, making interactions with technology more efficient and user-friendly and providing information, support, or services based on an understanding of the user’s current context or situation. This context can include factors like location, time, user preferences, device capabilities, and environmental conditions.
MulticoreWare’s Deep Learning algorithms capabilities enables intuitive gesture-based control and interaction with devices and surroundings. These systems recognize gestures associated with falls or distress and automatically trigger alerts to caregivers or emergency services.
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