Seed round raised from existing investors (True Ventures, BKR Capital, Centre for Aging and Brain Health Innovation, Health2047 and others) - $4.5M to date. Securing of MassAITC pilot funding helped in due diligence with investors for their seed round, and thus was critical to closing their funding including with Health2047, venture arm of the American Medical Association and with other early stage investors. Source: businesswire
"We are excited to partner with Moneta to make personalized, evidence-based cognitive rehabilitation the standard of care for our patients and families. Montana is vast and has the sixth oldest population in the nation. Moneta’s proven program is an accessible approach to proactive brain health for our aging demographic." Dr. Greg Tierney, President of System Clinical Operations at Benefis Health System. LAS VEGAS--(BUSINESS WIRE)--Moneta Health, a brain health company pioneering cognitive rehabilitation therapy through AI-powered delivery, today announced a $4.5 million funding round and a new partnership with Benefis Health System to expand access to cognitive care in neurology deserts. The company has signed a multi-year partnership with Benefis Health System in Montana and secured investment from venture capital firms including True Ventures and Health2047, the American Medical Association’s venture studio, to support its mission…
Authors: Tzu-An Song, Yubo Zhang, Ziyuan Zhou, Luke Hou, Masoud Malekzadeh, Aida Behzad, Joyita Dutta Abstract Polysomnography, the gold standard for sleep evaluations, involves complex setup and data acquisition protocols and requires manual scoring of sleep data. Smartwatches and other multi-sensor consumer wearable devices with automated sleep staging capabilities offer a promising and scalable alternative for routine and long-term sleep evaluations in individuals. We conducted a multi-night study using a smartwatch for sleep assessment and created an AI-driven automated sleep staging framework based on instantaneous heart rate (IHR) and accelerometry data using sleep stage labels based on electroencephalography (EEG) as the reference. 47 healthy adults were recruited to record their sleep for up to seven consecutive nights using an Apple Watch Series 6 and a Dreem 2 Headband. Our sleep staging framework relies on a…
Emerging Technology Category: The Emergency Technology category acknowledges innovators who have developed technology-driven tools showing great potential for improving care and/or the bottom line, even though they are not yet in the broad marketplace. Neursantys won top honors in this category for their pilot study with The Forum at Rancho San Antonio and LCS for their entry titled “NEURVESTA Vestibular Stimulation Therapy for Restoring Balance.” The study, involving 35 residents, showed that the protocol can enhance balance and lower the risk of falls, resulting in residents feeling more confident to participate in group outings and return to their exercise classes, and delaying the potential need for a higher level of care. Falls Prevention, Management or Detection: The Falls Prevention, Management or Detection category recognizes the use of technology that helps providers reduce the risk of…
BIDSleep helps you access wellness data from your Apple Watch, including heart rate, motion, blood oxygen, and sleep stages, all securely stored on your device. App Purpose: BIDSleep is a wellness app that helps users collect heart rate, blood oxygen (SpO₂), motion, and optional sleep stage data during rest or overnight sessions. It is designed solely for personal data logging and self-monitoring purposes. Source: https://apps.apple.com/us/app/bidsleep/id6747012248?platform=iphone
To the study team's knowledge, this is the first open-source four-class sleep staging model developed from a multi-night Apple Watch sleepstudy. SLAMSS-IFS, an advanced version of our previous SLAMSS model, for four-class sleep staging using IHR and accelerometry signals fromthese wearable devices. Key innovations in the model, including an intra-epoch learning LSTM, frequency information incorporation, andskip connections, contribute to substantial performance improvements over other SLAMSS variants and other state-of-the-art models. Ourresults show that SLAMSS-IFS outperforms competing models in overall accuracy, sensitivity, specificity, precision, weighted F1 score, weighted MCC, and most clinical sleep metrics. SLAMSS-IFS: The SLAMSS-IFS model builds on the original SLAMSS model with three additional components: an intraepoch learning sequence-to-sequence long short-term memory (LSTM (“I”), a frequency variable (“F”), and a skip connection (“S”). The intra-epoch learning LSTM processes temporal dependencies within individual epochs.…
Principal investigator, Amar Basu, professor of electrical and computer engineering at Wayne State University and CEO of TRACE Biometrics LLC, has received a National Institute on Aging R21 award to further validate the TRACE sensor against gold standard clinical orthostatic measures, which will build upon the pilot award's work towards securing FDA clearance. Project Summary: Orthostatic disorders, including orthostatic hypotension (OH), disproportionately affect older adults, presenting in 30% of older adults and up to 70% of nursing home residents. As OH is a major risk factor for syncope, falls, and cognitive decline, medical agencies stress the public health need for monitoring orthostatic vital signs (OVS) in at-risk individuals. This proposal investigates an NIA award-winning wearable device called TRACE, which addresses fundamental limitations of the current clinical standard, the blood pressure (BP) cuff: 1) The BP…