John Mastrototaro, Ph.D., biomedical engineer and CEO of Movano discusses strategies to improve data accuracy, the convergence of consumer wearables and medical remote monitoring devices and what healthcare providers are seeking in remote data delivery.
Inaccurate data entry, discomfort and privacy concerns are among the issues that developers and designers must address to realize the promise of medical wearables.
A review of the top six reasons there has been a dramatic increase in the adoption of remote care among seniors.
Patient-administered healthcare is one of the fastest-growing segments in the medtech industry. When the patient becomes the operator, usability requirements are vastly different than those of trained clinicians, which elevates considerations in the design process.
Building fruitful development partnerships between companies, governments and researchers will enable the most promising and impactful deployments in healthcare.
The pandemic caused a significant increase in telehealth and health tech adoption among all consumers and care professionals, especially those for older consumers and caretakers.
The market dynamics for telehealth and virtual care continue to evolve, and virtual care ecosystem players must understand how consumers have experienced these changes to better position themselves and design their solutions.
As the country emerges from the COVID-19 pandemic, it’s time to evaluate and assess lessons learned and find any possible silver linings derived from the crisis. This includes telehealth and the use of remote technology.
Today’s health monitoring and management systems rely on wires and batteries, and often are not continuously connected to an alert and communication system for patients and doctors. Wireless power will empower medical device manufacturers to develop sophisticated, smart IoT systems that will improve patient care and patient lives.
Healthcare services are expanding their ability to leverage data for use cases such as diagnostics, personalized treatment, imaging analysis, patient trend analysis, outcomes predictions, automation and more.