On August 10, 2022 at 9:00 am PT (noon ET), Alliance Member company Syntiant, along with Parks Associates and Canary Speech, will deliver the free webinar “Health IoT on the Edge: Accessible, Smart, Secure.” From the event page:
53% of US internet households own at least one internet-connected health product.
This webinar discusses how the value of health devices can be unlocked for applications in health and senior care via the use of low-power, edge-computing devices, especially designed for executing machine learning algorithms.
A new perspective is taking hold among care providers, payers, vendors, and patients that the home is a viable and valid location for health management and healthcare delivery. Demand for and deployment of virtual health solutions have grown exponentially, and consumers increasingly seek out their own health devices to own and use at home.
The quality of healthcare is often limited by the amount and quality of data available. Routine checkups and follow-up appointments oftentimes do not provide the insights and data that can support the best patient care. IoT healthcare devices overcome the limited sample size by continuously collecting and analyzing data. The use of predictive analytics and machine learning algorithms can turn real-time data into actionable and potentially life-saving insights and clinical assessments.
Examples of use cases powered by machine learning:
- Identify and avoid health crises
- Triage at-risk patients
- Assess patients for unidentified and undiagnosed medical conditions
- Detect health deterioration and dementia through speech patterns
- Predict falls or mobility declines in the elderly
All these use cases require continuous analysis of a tremendous amount of data. With many cloud-based solutions, where the health IoT device acts primarily for data collection and as a display, the bandwidth requirements for continuous data transmission and the latency involved in performing analytics in the cloud and sending back results can limit the effectiveness of solutions. New approaches to computing solve this problem by running the analytics on the edge device itself, which offers ultra-low latency, high reliability, and data privacy and security.
For more information and to register, visit the event page.