A New Era of Continuous Health
Monitoring and Clinical Intelligence

Introducing the TempleGuard:
The discreet wearable for long-time, continuous CVD monitoring.

Our Vision

Equipping patients, caregivers and physicians with non-stop, real-time remote patient monitoring of cardiovascular disease.

Our Mission

To build a discreet monitoring device fixed on any eyeglasses frame that collects crucial information, processes it via deep learning algorithms and makes it available at the right time.

Target Market​

9.7% of men
7.6% of women

Had CVD, diabetes mellitus, or received lipid-lowering or antihypertensive treatment*.

0 M
People

Died from CVD in 2018, representing 31% of all global deaths. Of these deaths, 85% are due to heart attack and stroke**.

Market potential

Health monitoring wearables

Market trends and drivers

Costly

Costly

TREATMENT AND HOSPITALIZATION
The average hospitalization cost of of a single CVD Patient in the US is $53K. newsarchive.heart.org
Why Eyeglasses can be smart.

Why Eyeglasses can be smart.

Average distance between Eyeglasses and Smartphone is below 1 meter throughout the day.

Inconsistency

Inconsistency

POOR MEASURING
30% of CVD monitoring devices are abandoned within 6–12 months, mainly due to inconvenience in the use Ernst & Young
Non-stop day-time  Monitoring via eyeglasses

Non-stop day-time Monitoring via eyeglasses

77% of the US population in the age group above 55, constantly wear eyeglasses. statista.com

Next Gen remote CVD monitoring

Our literature review shows that the area behind the ear is the best source for PWV and PTT measurements in the human body.

From temple tip to TempleGuard

The TempleGuard is using the part of the eyeglasses that is positioned right on the ideal measuring area and is usually concealed behind the ear.

The TempleGuard Difference

User Profiling

General user profile is set up upon App installation by asking relevant question

RAW USER DATA

Stored on flash memory of TempleGuard device and transmitted to smartphone using BLE (Bluetooth Low Energy) and further from Smartphone to Cloud.

ASSUMPTIONS BASED ON DEEP LEARNING

AI Model transfers raw data into assumptions which are validated by user feedback. Feedback is used to train data models.

MONITORING AND ALERTING

Qualified predection of unfolding CVD events through cross profiling, pre-defined gold standard tresholds and AI model.

USER PROFILING

General user profile is set up upon App installation by asking relevant question

RAW USER DATA

Stored on flash memory of TempleGuard device and transmitted to smartphone using BLE (Bluetooth Low Energy) and further from Smartphone to Cloud.

 

ASSUMPTIONS BASED ON DEEP LEARNING

AI Model transfers raw data into assumptions which are validated by user feedback. Feedback is used to train data models.

MONITORING AND ALERTING
Qualified predection of unfolding CVD events through cross profiling, pre-defined gold standard tresholds and AI model.

Business Model

R&D partnership
rnd1
Collaborators

Literature Review

Pulsewave’s Co-founders

Peter Weisz, CEO and Co-Founder

MBA from LMU, Munich. Born 1970 in Munich, Germany. Founder of Fitinstructor, an online Fitness plan database and Nutritional Planning software. Founder of WM Fahne 2006. Sold more than 4 Million Car flags during the FIFA 2006 World Cup in Germany and the 2008 FIFA EURO in Austria/Switzerland. As CEO of Swiss Nahrin AG, managed the successful turnaround of the Nahrin AG daughter companies in Russia, Ukraine, Estonia and Latvia between 2009 and 2013. Invented and developed the Findy Eyeglasses tracker, the smallest and lightest tracking device in the world. 3rd Runner up, EY Switzerland – Entrepreneur of the Year, 2006

Alexandr Shumilov, CTO
  • M.Sc. Diploma Engineering & Software Design, Ural Federal University, Russia
  • Specialization in Firmware/Embedded Systems
  • Embedded Software development team leader – Transas
  • Head of Software Design, Thommen Aircraft Equipment LTD
Adriele Alves Rocha, Chief Data Scientist
  • Bachelor in Mechatronic Engineering – Federal University of Uberlandia -Brazil
  • Aeronautics graduate at Beihang University – China
  • Past experiences: NASA, Airbus and John Deere
  • Specialization in robotics and data engineering
  • Specialization as AWS Data scientist @ AWS Start up Loft accelerator program
  • Focus on computing with Lambda and EC2, Storage using AWS S3, Analytics
    using AWS Glue, Redshift, AWS Data Stream and AWS Data Analytics using
    Python, Machine Learning with Amazon SageMaker

Collaborators and Advisors

Prof. Thomas Niederhauser - Professor for Biomedical Signal Processing and Control

Professor Niederhauser is research fellow at the Institute for Human Centered Engineering at the Bern University of Applied Sciences (BFH). After an industrial apprenticeship in Electrical Engineering, he received his diploma in Electrical and Communication Technology from the BFH in 2007 and his MSc degree in Biomedical Engineering from the University of Bern in 2009. From 2007 to 2009, he did industrial research at the Institute for Mechatronic Systems at the BFH. He then joined the ARTORG Center, Cardiovascular Engineering, where he performed research on low-power hardware and signal processing algorithms for long-term heart rhythm monitoring.

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In 2014, he earned his PhD degree in Biomedical Engineering from the University of Bern. After a short research visit at the Bern University Hospital, he was appointed as junior professor (tenure track) for Biomedical Engineering at the Institute for Human Centered Engineering at the BFH in 2015. He holds undergraduate lecturers in Feedback Control at the BFH and graduate lectures in Cardiovascular Technology at the University of Bern. He recently received a certificate as quality manager in medical technology.
His main research activities comprise novel technologies for long-term recording of physiologic functions. In particular, he focuses on the design of low-power hardware and signal processing algorithms for active medical devices intended for cardiac rhythm management and neurological monitoring of preterm infants.

Jon H. Hoem - Innosuisse Head Coach

Jon has, over the last 27 years, founded and developed several medical device companies including Medistim ASA, AtriCure Europe, Miracor Medical Systems and CorFlow Therapeutics, where he served as the CEO. He has a passion for early-stage cardio-vascular companies and has detailed insights into the preclinical and clinical development processes of these companies.

PD Dr. med Emrush Rexhaj - Clinical advisor

Associate Professor, Dr. Rexhaj achieved his PHD from Lausanne University in 2005. He worked as assistant physician in Lausanne and Martigny until 2008. From 2009 until 2011 he held a fellowship for internal medicine and extreme medicine at CHUV Lausanne. He received his training in Cardiology and Hypertension at the University Clinic, Bern between 2011 and 2016. He specializes in inner medicine and cardiology since 2016. Since 2017 he served as senior physician at the department of cardiology at the University Clinic, Bern. He received his post doctorate in cardiology in 2017. Since 2018 he heads the arterial hypertension and altitude medicine department at the University Clinic in Bern (Inselspital)

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