Red Hot Chili Steppers: Using SAS VDMML, OpenPose, & IoT Devices to Analyze Patient Motion and Health
Short 3-minute teaser video:
Our final video submission:
| Team Name | Team Red Hot Chili Steppers |
| Track | Track: Health, Track: Insurance, Track: IoT |
| Use Case | Using SAS AI and Machine Learning, we can build models to use this unique data to enable doctors, insurers, patients, athletes, and military personnel to track identities and monitor health in a new way by analyzing the person’s movement. Building upon the Berg Balance Assessment, this solution can be applied to numerous other health care use cases. |
| Technology | SAS AI and Machine Learning |
| Region | NA |
| Team lead | DJ Penix |
| Team members |
Pinnacle Solutions
Ontario Tech University
autonomous_ID
|
Every person walks in a way that is unique to them, creating a distinct signature to an individual’s identity. Using SAS AI and Machine Learning, we can build models to use this unique data to enable doctors, insurers, patients, athletes, and military personnel to track identities and monitor health in a new way by analyzing the person’s movement.
autonomous_ID has created the BIO_SOLE, a smart wearable shoe insole that can be placed inside of the shoes to collect continuous streaming data from over 192 sensors. Similar to a fingerprint, the BIO_SOLE insole can record a person’s unique way of standing, walking, running, or gait, and to create a unique signature to their identity. BIO_SOLE uses pressure sensors, accelerometer, gyroscope and circuitry to track every part of the movement, which can be influenced by body position, weight, injury, or disease.
There are numerous industry applications for Healthcare, however for the SAS Hackathon, the teams at Pinnacle Solutions, Ontario Tech University, and autonomous_ID will focus on building an application that can provide analysis on a variety of mobility, balance, and motion use cases from the BIO_SOLE insole, as well as other Internet of Things (IoT) devices that have gyroscopes, accelerometers, and pressure sensors.
We are planning to present various use cases and examples of visualizations, including data from the BIO_SOLE and other IoT sensors that can provide gait analysis, motion analysis, balance assessment, and categorization of various tasks such as walking, standing, running, or sitting as examples. By saving baseline and subsequent scores for patients, the application will also be able to determine improvements and worsening of potential health indications for each individual. This could indicate and detect early onset of various diseases and injuries.
The use for this application would have significant impact on health providers, health insurers, and patients. Once the modeling process has been developed, the application can be extended to numerous other health indications, including weight management, detection of disease such as diabetes, pain management, substance abuse, general health monitoring, among others.
Meet the Red Hot Chili Steppers team!
Top row: [Pinnacle Solutions] Scott Koval, Niketa Patel, Nam Chau, Dave Foster, DJ Penix, Frank Hack
Bottom row: [Ontario Tech University] Nitish Kumar, Chandra Kalahasthi, Navya Gudi, [autonomous_ID] Iltaf Kahn, Fred Vail, Todd Gray
@penixdj Can you please replace your YouTube links with direct uploads of your videos instead? You can do this by clicking the Video button in the toolbar:
