Robert Hager, Preveal Technologies, Inc. Hassan Ghasemzadeh, ASU. The goal of this proposal is to develop an Electroencephalography (EEG) neurofeedback (NFB) prototype system consisting of a headset and machine learning algorithm coupled with music, that can be used in the home to improve working memory.
James Mastrianni, The University of Chicago. Josh Kim, Adiona Health. This project seeks to validate a novel machine learning technique that analyzes motion data from an accelerometer in an Apple Watch to identify the onset of an agitation episode in a person with ADRD.
A TechCrunch released an article today on the a2 Pilot Awards and the a2 Collective, of which MassAITC is one of three member centers. Read more here: https://techcrunch.com/2023/01/09/a2-pilot-awards/.
The first cohort of seven MassAITC pilot projects has been announced. Details for the selected MassAITC projects are available here: https://massaitc.org/year1-pilots/. The list of selected pilot projects is also included below. The full MassAITC press release is available here. The next MassAITC pilot project competition is expected to open in May 2023. See the a2 Pilot Awards website for more details on the next pilot competition as well as the list of all Year 1 pilot projects funded by the a2 Collective centers. Testing a vocal biomarker platform for remote detection and monitoring of cognitive impairment in the home environment Erik Larsen (Sonde Health Inc.), Bradford Dickerson, Bonnie Wang (Massachusetts General Hospital) Developing real-world digital biomarkers from wearable sensors in Alzheimer’s disease, Jen Blankenship (VivoSense Inc.), Michael Busa (UMass Amherst) Vascular aging using infrasonic hemodynography…
Jane Saczynski, Northeastern University. Edward Marcantonio, Beth Israel Deaconess Medical Center. Acute illness presents in the most vulnerable organ in the body, among patients with dementia that organ is the brain and acute illness often presents first as delirium, an acute confusional state. This project will evaluate home monitoring devices as early indicators of acute illness in persons with dementia.
Anna Barnacka, MindMics Inc. This project will collect data for building and validating algorithms for analytics of vascular aging using Infrasonic Hemodynography with wearable earphones (the MindMics device).
Edward Jay Wang, UCSD. Given the prevalence of uncontrolled hypertension and additional challenges in the older adult population, it is essential that measurement of BP be done easily and accurately. This project will develop an ultra low cost approach to converting the billions of smartphone cameras, even the cheapest ones, into blood pressure monitors that can be used by older adults at home.