Edge AI has emerged as a powerful technology with the potential to transform various industries, and healthcare is no exception. By processing data on local devices, edge AI reduces the reliance on central servers or cloud infrastructure, enabling faster decision-making and improved patient care. It can provide practical solutions to some of the most pressing challenges in healthcare, with a focus on innovative devices that have recently hit the market.
How edge AI is transforming healthcare, and what’s coming next
Edge AI has enabled the development of advanced wearable devices that offer personalized healthcare solutions. These devices continuously monitor a person's health, providing real-time feedback and personalized recommendations. Some notable examples include:
Oura Smart Ring: This sleek ring tracks sleep, activity, and recovery data. By leveraging edge AI, the Oura Smart Ring can provide personalized insights into a user's sleep patterns and overall well-being, helping them make informed decisions about their daily routines.
Nowatch: Focused on mental well-being, Nowatch uses edge AI to analyze biometric data, such as heart rate variability, to monitor stress levels and provide real-time feedback to users. This helps individuals better understand their mental health and adjust to improve their overall well-being.
Know Labs: This innovative company has developed a non-invasive glucose monitoring device using edge AI technology. By analyzing a user's glucose levels in real-time, Know Labs' device allows for better management of diabetes without the need for painful finger-pricking.
Hyfe: This unique application utilizes edge AI to track and quantify coughs. By analyzing the frequency and patterns of a user's cough, Hyfe.ai can help identify potential health issues and provide valuable information for medical professionals.
All four of these companies are partnering with Edge Impulse to help develop and strengthen their algorithms and bolster their device viability.
Edge AI has made significant strides in the field of diagnostics. For example, portable ultrasound devices can now analyze images locally, providing instant results and reducing the time needed for diagnosis. Similarly, AI algorithms can analyze medical images, such as X-rays or CT scans, on local devices for early detection of diseases such as cancer, enabling timely treatment and improving patient outcomes.
With the integration of edge AI, virtual health assistants are becoming more sophisticated and accessible. They can offer personalized support to patients, including medication reminders, appointment scheduling, and answering general health-related queries. These AI-powered assistants can process and store data on the device, ensuring patient privacy while providing real-time support.
Moving into the future, Edge AI stands to help expedite drug development and enable personalized medicine by analyzing patient data and identifying individual treatment plans on location. Through advanced data analytics, edge AI could quickly help identify novel drug candidates and optimize clinical trial design, while retaining more privacy protection than cloud-based processes. Additionally, by analyzing a patient's genetic information, edge AI could assist in tailoring treatment plans to meet individual needs, improving the overall effectiveness of medical interventions.
Edge AI-enabled devices also have the potential to support mental health initiatives, analyzing speech patterns, facial expressions, and other biometric data to identify signs of distress, such as stress, anxiety, and depression. These devices could provide real-time feedback and support and connect users with professional help when needed.
Smart pill bottles and other connected devices could also use embedded machine learning to track medication usage and provide reminders for patients to take their medication. This technology would help improve drug adherence and reduce the risk of complications due to missed doses.
Edge AI is already transforming the healthcare industry with its practical applications and the introduction of cutting-edge devices. Combined with new advancements, this technology will address critical challenges in healthcare while ensuring patient privacy and reducing response time. As it continues to evolve, the integration of edge AI in healthcare will undoubtedly lead to improved patient care and outcomes.
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Mike Senese is the Director of Content for Edge Impulse. Previously the Executive Editor of Make: magazine and a senior editor at Wired, he spends his time tinkering with the latest technology tools. You can find him at mikesenese.com.