Enhancements address significant clinical
enterprise need in wearables for a variety of healthcare
applications
PLEASANTON, Calif.,
June 13, 2024 /PRNewswire/ --
Movano Health (Nasdaq: MOVE) announced
major advances in the accuracy of its heart rate in motion
algorithm following the implementation of deep learning into the
processing. The Company recently released an engineering accuracy
study directed by Movano Health Founder and CTO Michael Leabman, Enhanced Heart Rate in Motion
Accuracy with the Evie Ring Using Advanced Deep Learning
Algorithms, which demonstrates the value of deep learning
integration into heart rate (HR) algorithms for improved
accuracy.
"Utilizing deep learning is significantly better than standard
techniques as it is the optimal solution for removing the effects
of motion, eliminating the noise and motion artifacts in the
optical signal," said Leabman. "We believe that this is a first of
its kind implementation and an innovation that has the potential to
enhance the reliability of wearable health monitors, providing
users with more accurate and consistent heart rate
measurements."
The study was conducted with 65 subjects, completing 7-10
sessions of various activities including sleeping, resting,
walking, running, climbing stairs, working out at the gym and
swimming. Data was collected with the Evie Ring and a Polar H7
chest strap used as a control device. The results demonstrated a
high correlation with the Polar H7 chest strap outputs across a
diverse data set, confirming the reliable reporting of heart rate
by Evie's HR algorithm across all activities.
To overcome the challenges of measuring heart rate from PPG
signals in wearables, Evie's HR solution combines the best from the
signal processing world as well as recent advances in AI-based Deep
Learning.
- Optimally filtering out motion artifacts and more accurately
tracking heart rate through development of AI algorithms in a
specific, novel Deep Learning solution.
- Removing motion artifacts from the PPG signal by leveraging
both PPG and 3D accelerometer data.
- Enhancing the signal-to-noise ratio (SNR) through Deep
Learning.
The Company plans to convert all Evie Ring algorithms including
sleep, respiration, heart rate variability (HRV), and blood oxygen
saturation (SpO2) through this same process.
About Movano Health
Founded in 2018, Movano Inc.
(Nasdaq: MOVE) dba Movano Health is developing a suite of
purpose-driven healthcare solutions to bring medical-grade data to
the forefront of wearables. Featuring modern and flexible form
factors, Movano Health's devices offer an innovative approach to
delivering trusted data to both customers and enterprises,
capturing a comprehensive picture of an individual's health data
and uniquely translating it into personalized and intelligent
insights.
Movano Health's proprietary technologies and wearable medical
device solutions will soon enable the use of data as a tool to
proactively monitor and manage health outcomes across a number of
patient populations that exist in healthcare. For more information
on Movano Health, visit https://movanohealth.com/.
Forward Looking Statements
This press release contains
forward-looking statements concerning our expectations,
anticipations, intentions, beliefs, or strategies regarding the
future. These forward-looking statements are based on assumptions
that we have made as of the date hereof and are subject to known
and unknown risks and uncertainties that could cause actual
results, conditions, and events to differ materially from those
anticipated. Therefore, you should not place undue reliance on
forward-looking statements. Examples of forward-looking statements
include, among others, statements we make regarding plans with
respect to the commercial launches of the Evie Ring and Evie Med;
planned cost-cutting initiatives; anticipated FDA clearance
decisions with respect to our products; expected future operating
results; product development and features, product releases,
clinical trials and regulatory initiatives; our strategies,
positioning and expectations for future events or performance.
Important factors that could cause actual results to differ
materially from those in the forward-looking statements are set
forth in our most recent Annual Report on Form 10-K and any
subsequent Quarterly Reports on Form 10-Q, and in our other reports
filed with the Securities and Exchange Commission, including under
the caption "Risk Factors." Any forward-looking statement in
this release speaks only as of the date of this release. We
undertake no obligation to publicly update any forward-looking
statement, whether written or oral, that may be made from time to
time, whether as a result of new information, future developments
or otherwise.
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SOURCE Movano
