Cognitive IoT for Heathcare - Strategy Areas
A new health frontier lies in the ability of our surrounding environments to learn and collect information from our daily activities. Routine movements that we do without thinking – such as sitting, standing, opening and closing doors – can be analyzed and interpreted to monitor and even help predict an individual’s level of well-being or the progression of a disease. Understanding how a person behaves naturally in their home can be important since, when compared to chaotic settings such as the office, physiological and behavioral data from the home is believed to be a more accurate representation of a person’s overall health.
The Cognitive IoT for Healthcare team focuses in three key strategy areas;
- Fingernail Sensor - an IBM developed sensor that attaches to the fingernail to measure forces and movement. IBM algorithms intrepret these measurements to identify motions, gestures, finger-writing, grip strength, and activation time, as well as more complex idioms consisting of multiple grips, are identified and quantified. We demonstrate the use of this technology as a human-computer interface, clinical feature generator, and means to characterize workplace tasks.
- Hearable - An earbud-type wearable (A hearable) with vital parameter sensors for early detection and prevention of heat-stroke;
- IoB Hub - A edge hub to aggregate signals from a range of wearables and interact with a patient or doctor.
- Motion Analysis (Gait)
- Dynamic Edge-Fabric environmenT (DEFT)-a new fog/edge platform with dynamic switching to the cloud that automatically learns where best to execute each task based on real-time system status and task requirements, along with learned behavior from past performance of the available resources. Such an intelligent environment is an essential part of the exploding IoT ecosystem.
- Aging - Ubiquitous computing and the IoT are enabling the possibility to provide remote health care services through networks of environmental and personalized sensors.
- Chronic Pain - Understanding an individual's state of pain and the potential effectiveness of treatment options.
- Stress - applying our IoT for healthcare fabric to quantify an individual's ability to make critical decisions and to assess and predict the reduction of this ability by the different intensities and categories of stress. Our IoT system can perform inference at the edge and thus overcome computation and connectivity limitations
- Epilepsy - applying our cognitive IoT for healthcare to build patient-specific Seizure Detection, Prediction and Causal Inference Systems that are integrated with Watson Health and Watson IoT. Our vision is to bring precision medicine to epilepsy.