AI has become part of daily life in medical device usage and data analysis.
COVID-19 has accelerated the need for medical device and healthcare AI. From handheld devices for instant blood and at home rapid testing through to large form factor equipment such as next generation of MRI and CT scanners, the world will never be the same, nor will be the way that people consult with medical practitioners for health checks and diagnosis.
Smart wearable medical devices deliver fast and accurate early detection of medical emergencies (such as stroke or cardiac problems) or onset of conditions needing treatment. In consumer wearables, activity recognition enhanced with AI improves performance measurement, fitness advice, therapeutic monitoring, and elderly care (e.g., fall detection).
AI is Coming out of the Cloud and into the Edge
Frameworks like TensorFlow Lite support development on embedded computing platforms enable building lightweight inference engines to handle tasks such as:
- Activity detection
- Gesture discovery
- Repetitive tasks
At the point of presence.
Edge AI can deliver performance advantages such as:
- Lower latency
- Lower power consumption
- Greater privacy
By eliminating data-intensive interactions with AI applications in the cloud.
But that’s not all. These edge platforms will outperform, outclass, and replace conventional applications currently performed using scalar processors.
What are the Top Applications for Edge AI?
Recognising that many smart devices already rely on capabilities like:
- Voice recognition
- Facial recognition
- Motion detection
Edge AI will enable them to become more responsive, more adaptive, more accurate, more richly featured, more easily portable (or wearable), more affordable, and use less power.
In the medical device world where precision and accuracy are vital, many OEMS are adopting Edge AI as they can understand the immense benefits that it brings.
There is a tremendous opportunity for start-ups founded on skills in AI and machine learning to disrupt the old order and deliver new solutions that are faster, more flexible, more sustainable, and more affordable. Equally, established players need to modernise using this new technology or risk being left behind.
Find out more in our article How Edge AI will change the world of industrial computing.