Medical Wearables
This evening, I had the chance to attend a medical wearables event hosted by IEEE. There were two presenters, who presented an overview of applications and their involvement in the design and feasibility of such solutions. The field is interesting because it's at the intersection of two orthogonal fields: computer science and biology, more specifically medicine.
The first speaker, Don Aoki, presented an accessible solution for consumers for diagnosis of sleep disorders. The solution presented an accessible and convenient product individuals can use for sleep monitoring. The product leverages existing measurement devices, such as EKG, EEG, pulse oximeter, among others, in the assessment of an individual's sleep. These measurements are a subset of the more comprehensive range of measurements made by a polysomnograph made in a clinical setting. However, by making an in-home, affordable solution, the concept bypassed the financial and mental inconveniences of the latter. The solution was designed with affordability and convenience in mind. Medical devices, as opposed to monitoring devices, are more thoroughly regulated by the FDA, in order to ensure that the product meets its claims. Interestingly, the classification of a product as a medical device has a significant impact on the price, as medical products are more in-demand than simply monitoring tools. In addition, red tape and stringent regulation by the FDA presents another challenge to be overcome.
The second speaker, Walt Maclay, presented an overview of some design issues and considerations in the production of medical wearables. Like Don, Walt brought up the intention of wearables to be convenient first and foremost, enabling their accessibility and success with patients. He discussed a total of eight different measurements that could be made using medical wearable technology, as well as the advantages of different methods of measurement. He also brought up the limitation of battery life, which limits the amount of computation that can be performed on the edge. With such a constraining factor in mind, even lighting up an LED can become a computational roadblock, and the consumption of power for each sensor must be accounted for down to the milliwatt. In addition, it's also crucial to provide accurate measurements, which doesn't always line up well with convenience.
The first speaker, Don Aoki, presented an accessible solution for consumers for diagnosis of sleep disorders. The solution presented an accessible and convenient product individuals can use for sleep monitoring. The product leverages existing measurement devices, such as EKG, EEG, pulse oximeter, among others, in the assessment of an individual's sleep. These measurements are a subset of the more comprehensive range of measurements made by a polysomnograph made in a clinical setting. However, by making an in-home, affordable solution, the concept bypassed the financial and mental inconveniences of the latter. The solution was designed with affordability and convenience in mind. Medical devices, as opposed to monitoring devices, are more thoroughly regulated by the FDA, in order to ensure that the product meets its claims. Interestingly, the classification of a product as a medical device has a significant impact on the price, as medical products are more in-demand than simply monitoring tools. In addition, red tape and stringent regulation by the FDA presents another challenge to be overcome.
The second speaker, Walt Maclay, presented an overview of some design issues and considerations in the production of medical wearables. Like Don, Walt brought up the intention of wearables to be convenient first and foremost, enabling their accessibility and success with patients. He discussed a total of eight different measurements that could be made using medical wearable technology, as well as the advantages of different methods of measurement. He also brought up the limitation of battery life, which limits the amount of computation that can be performed on the edge. With such a constraining factor in mind, even lighting up an LED can become a computational roadblock, and the consumption of power for each sensor must be accounted for down to the milliwatt. In addition, it's also crucial to provide accurate measurements, which doesn't always line up well with convenience.
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