Relying on wearable devices such as smartwatches or smartbands to prevent health issues and ultimately replacing medical professionals can be very dangerous. While these devices offer convenience and quick access to health data, they may lack accuracy and depth in their assessments. Misinterpretation of data or failure to detect critical health indicators could lead to delayed or inaccurate diagnoses.

In simple terms, smartwatches have yet to replace clinically validated equipment in hospitals as they are not able to provide the same accuracy and reliability in medical procedures. However, researchers are actively seeking ways to integrate these devices into clinical practice, considering their presence as an aid, rather than a full-fledged substitute.

A project in the UK has investigated whether the Garmin Venu 2 and a dedicated app could streamline medical processes, potentially saving time for healthcare professionals.

The theory behind the idea: The Six Minute Walk Test

The Six Minute Walk Test (6MWT) is a vital tool for diagnosing and monitoring various cardiovascular conditions, including potentially fatal ones such as Pulmonary Hypertension. Project leader Dr. Joseph Newman highlights its importance as a marker of cardiopulmonary function, also emphasizing its role in clinical practice worldwide.

[The test has been] a cornerstone of hospital practice and clinical trials for decades all around the world as […] a marker of how well the heart and lungs are working

But what does this test require? And how does it work?

The test involves a patient walking continuously for six minutes on a flat surface, while professionals monitor heart rate and blood oxygen levels. Despite its reliability, many healthcare professionals acknowledge its shortcomings and aim to innovate by shortening and digitizing the test for remote use.

And that’s where Garmin’s wearable technology and devices come in. Researchers wanted to revolutionize the test by potentially reducing it to just one minute and enabling patients to perform it at home using the Garmin Venu 2. Patients were instructed to walk outdoors, allowing for a more natural assessment of their physical capabilities.

The role of the patient at the center of the healing process

Giving patients the tools to complete tests at home has many benefits, including an improved representation of their daily lives and simpler long-term health tracking. Dr. Newman sees real value in providing patients with tools like an app and smartwatch for monitoring progress, potentially reducing the frequency of hospital visits.

We can see real value in providing patients with pulmonary hypertension with an app and smartwatch to monitor their progress. It’s unlikely to ever fully replace the need for in-person hospital reviews, but it will likely reduce their frequency.

Initial study results suggest that shortening the test to one minute does not compromise its accuracy, while patients are more likely to comply with regular testing when done at home.

While advancements like this hold potential for enhancing patient care and reducing healthcare burdens, they should always be viewed within the context of comprehensive medical oversight and personalized treatment plans. As we embrace the evolving landscape of digital health solutions, it is important to prioritize accuracy, patient-centric care, and the collaborative integration of technology with traditional medical practices.

Among the most dominant models on the market, is certainly the Apple Watch, which has now rolled out its series 9 smartwatch. The Apple Watch has always allowed users to closely monitor their health conditions, generating very useful data that has often helped to speed up or even improve the treatment provided by healthcare facilities.

The new design of the Apple Watch Series 9 will grant users the options to access and log their healthcare data, while also controlling the Watch using their index finger and thumb via blood flow sensors. The new Apple Watch has been released with a comprehensive set of features, including heart rate monitoring, blood oxygen detection, ECG readings, sleep tracking, fall detection, loud noise monitoring, and built-in temperature sensing, all of which were initially introduced in previous models.

Furthermore, it now incorporates a Crash Detection feature that utilizes the watch’s gyroscope, accelerometer, and an advanced sensor-fusion algorithm to identify severe car accidents. In the event of a crash, the Apple Watch promptly checks in with the user, and if no response is received within 10-seconds, emergency services are automatically alerted.

Thanks to the new features, users can interact with their health data by utilizing Siri’s health-related queries. This allows them to get data like their previous night’s sleep duration or their average heart rate while walking. Additionally, users have the option to verbally input information, including their weight, menstrual cycle data, and medication taken, a positive step forward for elderly care.

New features and improvements

With the advancement of technology and the introduction of artificial intelligence into the healthcare ecosystem, devices like the Apple Watch have significantly improved their accuracy. The Series 9, which features twice the brightness of the Series 8, includes a SiP S9 chip capable of storing and processing machine-learning tasks twice as fast as the previous version, all while providing a total battery life of 18 hours.

The Apple Watch introduces a feature called ‘double tap‘, which will allow users to answer, end a phone call or control the main buttons to play certain types of content.

“[The Series 9] features a magical new way to control your Watch with double tap, faster on-device Siri that lets you securely access health data, precision finding for iPhone and a brighter display, all enabled by the S9 SiP, our most powerful chip ever in an Apple Watch. And it’s Apple’s first-ever carbon-neutral product,” said Jeff Williams, Apple’s chief operating officer.

With the release of the new Apple Watch, the Californian company also renewed its pledge to become a carbon-neutral company by 2030. In this regard, they stated that the Apple Watch uses renewable materials at every stage of product development and shipping, including the use of 100% recycled cobalt in the battery. This makes the Series 9 the first carbon-neutral product ever developed by Apple.

The research, funded by the JDRF Foundation, the Leona M and Harry B Helmsley Charitable Trust, and the National Institutes of Health, marks a significant advancement in diabetes management.

Background: People with type 1 diabetes face unique challenges when engaging in physical activities like exercise due to the potential for dangerous fluctuations in blood glucose levels. While exercise is known to rapidly lower glucose levels, there has been a lack of integration between ubiquitous wearable fitness sensors and AID systems. This study aimed to test whether AID systems could use real-time fitness data to automate insulin adjustments, reducing the risk of hypoglycemia during exercise and daily life.

Methodology

The study included individuals who met specific inclusion criteria, such as having a diagnosis of type 1 diabetes for at least 1 year, being between the ages of 21 and 50, being physically capable of aerobic exercise, using an insulin pump for at least 3 months with stable settings for 2 weeks, and having a baseline HbA1c level of 10·0% or lower. Additionally, participants needed to live with an adult aged 18 years or older within 40 miles of OHSU and have a total daily insulin requirement of less than 139 units per day to ensure that meal insulin could be delivered within 20 minutes.

It commenced with a screening visit conducted within 12 weeks before a 1-week run-in period. During this visit, participants provided written informed consent, underwent eligibility screening, and had their HbA1c levels measured. Additionally, an electrocardiogram (EKG) was performed. Once eligibility was confirmed, participants engaged in a 1-week run-in period during which they received training on using the Dexcom G6 continuous glucose monitoring system (CGM). Subsequently, participants arrived at the OHSU inpatient research unit to initiate the first 76-hour treatment phase.

Participants were assigned to use either an AID that detects exercise, prompts the user, and adjusts insulin during exercise using an exercise-aware adaptive proportional derivative (exAPD) algorithm or an AID that automates insulin adjustments using fitness data in real-time through an exercise-aware model predictive control (exMPC) algorithm. Both algorithms ran on an iPancreas system, incorporating commercial glucose sensors, insulin pumps, and smartwatches.

Overview of iPancreas Test Platform

iPancreas is an innovative and adaptable system designed to facilitate the swift development of closed-loop and decision support algorithms, as well as user interfaces for effective glucose management. This system is modular, licensable, and available for open access, offering researchers and developers a versatile tool for prototyping glucose management solutions.

The iPancreas system comprises several key components, including:

1. Custom iPancreas App: The system operates through a custom-designed application that runs on a Samsung smartphone from Suwon-Si, Korea. This app serves as a central control hub for managing glucose levels and insulin delivery.
2. Dexcom G6 CGM: The system integrates a Dexcom G6 continuous glucose monitoring (CGM) system, which wirelessly provides real-time glucose data to the smartphone.
3. Research Version Insulet Omnipod: An Insulet Omnipod, designed for research purposes, is included in the system. It is responsible for insulin delivery based on the control algorithm’s calculations.
4. Polar M600 Smartwatch: The iPancreas setup includes a Polar M600 smartwatch from Kempele, Finland. This smartwatch captures essential data such as heart rate and accelerometry, which can be valuable for monitoring physical activity and its impact on glucose levels.
5. Custom-Developed Cloud Monitoring and Data Acquisition Repository: To manage and analyze the data generated by the system, a custom-developed cloud-based monitoring and data acquisition repository is employed. This repository runs on Amazon Web Services (AWS) in Seattle, WA, USA, ensuring efficient data handling and storage.

The core functionality of iPancreas involves wirelessly receiving CGM data and data from the Polar M600 smartwatch through the smartphone. The system’s control algorithm processes this data to calculate the appropriate insulin dose, which is then transmitted wirelessly to the Insulet Omnipod for insulin delivery. Additionally, iPancreas incorporates a meal bolus calculator to assist users in managing their insulin dosage in response to meals.

Overall, iPancreas offers a versatile and comprehensive platform for the development and testing of glucose management solutions, with the potential to advance diabetes care and treatment options.

Outcomes

The time spent below the target glucose range (39 mmol/L) during the primary in-clinic session between April 13, 2021 and October 3, 2022 was compared in the research. There was no significant difference in time spent below the target range between the exMPC and exAPD groups. The exMPC group, on the other hand, had lower mean glucose levels after two hours of in-clinic activity. Both algorithms met clinical time in range objectives, with exMPC achieving 71.2% and exAPD achieving 75.5%. However, as compared to the run-in period, the exMPC group dramatically reduced time spent below the goal range. During the trial, no adverse events were noted. Secondary outcome measures included determining the amount of time spent within the target glucose range, the amount of time spent over the goal range, and the number of rescue carbs required each day in reaction to hypoglycemia.

Conclusions

The study demonstrated that both exMPC and exAPD algorithms, which incorporate exercise metrics, yield similar glucose outcomes in individuals with type 1 diabetes.
During the primary in-clinic session, both algorithms showed comparable time spent in the target glucose range and time below the target range. However, the exMPC algorithm outperformed the exAPD algorithm in the two hours following the start of structured exercise, significantly lowering mean glucose levels without a significant increase in time spent below the target range or experiencing very low glucose.

This represents a pioneering effort in integrating exercise metrics as continuous inputs into an automated insulin delivery system to modify insulin dosing under real-world, free-living conditions. The exMPC algorithm could adapt to exercise events throughout the day, including activities of daily living. Both algorithms effectively maintained participants above 70% of the time within the target glucose range and kept time spent below the target range below 4%, aligning with recommendations from the American Diabetes Association.

However, the study has several limitations, including a relatively short duration, limited evaluation of structured exercise, potential noise introduced by the FDA’s requirement for an in-clinic evaluation, and the specificity of the results to one type of fitness watch, the Polar M600. Further research is needed to address these limitations and validate the findings in broader contexts.

Graduates from the University of Bath have introduced a groundbreaking women’s safety smartwatch app, Epowar, that employs heart rate and body motion monitoring to detect distress and automatically send an emergency alert in the event of an attack.

The Epowar app, designed primarily for women’s safety, addresses a major drawback of traditional rape alarms and personal safety devices: the need for manual activation, which may not be feasible during a violent assault.

This innovative smartwatch app employs artificial intelligence (AI) to respond instantly when a user is attacked while walking or running alone. The app identifies distress, sends an alert to the user’s contacts, and automatically records and stores critical evidence, including microphone data, GPS location, vital signs, and movement, in a secure cloud system.

Starting June 1st, the app is available on the UK App Store, with plans to expand its compatibility to other devices like Fitbit, Android, and Garmin later this year.

E-J Roodt, co-founder of Epowar, expressed excitement about the app’s launch after three years of rigorous research and development. “We believe it will make a significant contribution to women’s safety. The key is that it all happens automatically – an assailant would have little or no time to prevent this, which is not always possible with conventional panic buttons, rape alarms, or your mobile phone.“

Roodt noted that many women are afraid to walk or run alone due to the fear of violence, and she believes that technology like Epowar can help women regain a sense of power and control.

The idea behind the Epowar app

The inspiration for the app came to Roodt, a University of Bath BSc Business graduate, while jogging in a poorly lit park, worrying about the risk of an attack. Aware of advances in wearable technology, she wondered if concepts used to detect heart attacks could be applied to women’s safety.

She shared her ideas with Maks Rahman, an engineering student, and together they co-founded Epowar.

Supported by the University’s Enterprise and Entrepreneurship program, which provided funding and a business mentor, they began developing Epowar while still students. After graduating – Roodt in 2022 and Rahman a year earlier- they continued full-time development.

The AI-powered system was built based on extensive research into detectable responses to physical distress and the analysis of thousands of samples of physiological and motion data. The AI models can distinguish distress incidents from regular activities like walking.

Rahman emphasized the team’s commitment to addressing privacy concerns often associated with security apps. Epowar’s software does not track or identify the wearer until an alert is issued. While users currently activate the app for specific journeys where they anticipate potential risks, future versions will allow continuous use. The collected data is anonymized and used to improve the app’s performance.

“I’m used to walking my female friends home whenever it’s late or they feel unsafe. I have two younger sisters, and I wondered what it would be like for them and if someone would do the same. I hope they use Epowar to be safe and also independent,” Rahman said.

Epowar represents a significant advancement in personal safety technology, providing women with a reliable and automatic means of summoning help in times of distress.

“We are keen to find ways to make this as affordable and accessible to as many women as possible and could envisage a system where organisations, such as schools or universities, make available such software to groups for example. We hope people will recognise the ability to automatically alert contacts as a game-changer in a world where such software seems increasingly necessary,” Roodt said.

Background

Type 1 diabetes, an autoimmune disorder, impairs the pancreas’ ability to produce insulin, which is essential for regulating blood glucose concentrations. People with this condition often require exogenous insulin to maintain normal glucose levels. Automated insulin delivery (AID) systems have gained traction in recent years, comprising a combination of continuous glucose monitoring (CGM), insulin pumps, and control algorithms. These systems automate insulin delivery based on sensed glucose levels, but there’s a persistent need for improvement, as achieving target glucose levels and avoiding hypoglycemia remains a challenge for many.

Methodology

The study, published on The Lancet Digital Health and conducted at the Harold Schnitzer Diabetes Health Center clinic at Oregon Health and Science University, focused on harnessing wearable fitness sensors to enhance AID systems’ performance. Two distinct AID algorithms were evaluated: the exercise-aware adaptive proportional derivative (exAPD) algorithm and the exercise-aware model predictive control (exMPC) algorithm. Both algorithms integrated real-time fitness data from smartwatches to inform insulin dosing and counter hypoglycemia during exercise and daily activities.

27 participants with type 1 diabetes were enrolled in the study. These participants underwent a crossover design, where they experienced both exAPD and exMPC algorithms in different sessions. The primary outcome measured was time spent below a certain glucose range (<3.9 mmol/L) during the primary in-clinic session. The secondary outcomes included mean glucose levels and time spent in the target glucose range (3.9–10 mmol/L).

Results

The results indicated that there was no significant difference between the exMPC and exAPD algorithms in terms of time spent below the target glucose range or time spent in range during the primary in-clinic session. However, in the two-hour period following the start of in-clinic exercise, the exMPC algorithm demonstrated lower mean glucose levels compared to the exAPD algorithm. Across the entire 76-hour study duration, both algorithms successfully achieved clinical time in range targets, with significantly lower time spent below range compared to the run-in period.

This study’s outcomes indicate a step forward in optimizing automated insulin delivery for individuals with type 1 diabetes. By incorporating wearable fitness sensor data, AID systems show potential for enhancing glucose outcomes and reducing hypoglycemia risks during exercise and daily activities. The integration of exercise metrics from wearable fitness sensors into future AID systems could open doors to safer and more effective exercise management for those living with type 1 diabetes.

Funding for this study was provided by the JDRF Foundation, the Leona M and Harry B Helmsley Charitable Trust, and the National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. The findings highlight ongoing advancements in health technology that aim to improve the quality of life for individuals with chronic conditions.

It reviews their methods and technologies and explores the evidence supporting their use as diagnostic and monitoring tools in various cardiovascular conditions such as hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. When used correctly, these devices can improve healthcare and support research efforts.

Disease assessment by physicians

To effectively predict, prevent, diagnose, and treat cardiovascular diseases, physicians require an assessment of symptoms, activity levels, comorbidity, and contextual information. This is before prescribing targeted investigations and treatment recommendations. Wearable technologies have the potential to enhance cardiovascular medicine care.
The authors discuss accessible devices available to the public, the underlying sensor technologies, the data they collect, and their applications. These tools offer a perspective on the potential integration of these technologies into cardiovascular healthcare. They highlight the challenges to address and the studies required to confirm their utility. Including wearable clothing, apparel, and cutaneous patches and their applications in clinical research in cardiovascular medicine.

The article emphasizes the importance of safety, accuracy, reliability, and reproducibility for all devices claiming to measure human physiology. For instance, blood pressure devices must adhere to strict guidelines provided by standards organizations. In this way, patients and healthcare providers can trust health apps data to identify cardiovascular disorders. The authors suggest an increased involvement of clinical bodies in the development of regulatory guidelines and evaluation methods.

Importance of symptom

Medical decision-making relies on symptom context, traditionally obtained by asking patients to recall their activities when experiencing symptoms. Subjective recall can be misleading, especially for patients with memory or communication difficulties. Mobile and wearable devices allow users to record symptoms and physical parameters simultaneously, offering more accurate and objective information. By using self-reported questionnaires, smartphone data, and wearable movement sensors, researchers have successfully applied this approach to mental health and Parkinson’s disease research. There is potential to identify patients who require further assessment or monitoring by distinguishing cardiac symptoms from non-cardiac symptoms.

Physical activity plays a significant role in the classification and treatment decisions of cardiovascular diseases such as heart failure and angina. Subjective self-reporting of physical activity levels is imprecise, and wearable device data provide objective measurements over extended periods. By measuring step counts, accelerometers can quantify physical activity, while GPS can track speed, location, and terrain over time. Patients’ specific data allows for more personalized medicine, including tailored exercise advice and monitoring treatment response.

Decision-making process

Wearable devices in clinical decision-making pose challenges and require validation. Despite numerous studies, wearable devices have yet to demonstrate improvements in defined medical outcomes. This highlights the necessity for further research to identify risks and benefits for patients and healthcare systems. Medical training will need to address these issues as evidence continues to grow and incorporate the complexities of handling large volumes of diverse device data.

The regulatory landscape for digital healthcare will need to keep pace with these advancements, while public trust and acceptance of wearable technology are crucial. Wearables could reduce healthcare inequalities if they were affordable and accessible to all. This is without discriminating against individuals who may face challenges using the technology due to unfamiliarity with electronic devices or health conditions.

Combining wearables with telemedicine has the potential to revolutionize community care, leading to a decrease in acute hospital admissions and healthcare spending. In conclusion, wearable technology has the potential to transform routine clinical consultations by providing standardized objective parameters of health and quality of life. This was gathered over an extended period. Wearable devices have shown promise in cardiovascular diseases, but they are still in their early stages. Wearable data can personalize and enhance cardiovascular disease management, ultimately improving outcomes for individuals and populations.

– In December, Novosound signed a commercial partnership agreement with PAVmed Inc., the Nasdaq-listed diversified medical technology company, to develop technology aimed at advancing intravascular imaging

– Novosound has hired former Intel executive David Jolliffe as CFO

GLASGOW, Scotland–(BUSINESS WIRE)–Ultrasound sensor specialist Novosound sees “massive opportunity” for its wearable technology in North American markets, having developed and commercialized a wireless wearable ultrasound platform with customer-led applications across healthcare, wellbeing, and fitness monitoring.

Dave Hughes, CEO and Co-founder, Novosound, said: “Recently, groundbreaking advancements in ultrasound technology have emerged, such as the recent work by the University of California San Diego into ultrasound system-on-patch (USoP) tech and the Internet of Medical Things (IoMT). In this revolution towards accessible, wearable, healthcare devices, Novosound stands at the forefront, demonstrating that its commercially available technology is an integral part of this narrative”.

In December, Novosound signed a commercial partnership agreement with PAVmed Inc., the Nasdaq-listed diversified medical technology company, to develop technology to advance intravascular imaging. The PAVmed agreement furthers Novosound’s move into healthcare and its regional expansion into North America. Previous contract wins include with aerospace giants BAE Systems and GE Aviation, and Israeli-based digital health company dSound.

Novosound recently hired former Intel executive David Jolliffe as Chief Financial Officer. Jolliffe has extensive international experience, and has held board positions with a number of public limited companies and private equity-backed businesses. Jolliffe was the CFO at Optoscribe, a Scottish technology company that developed 3D lasers for the telecommunications sector and was acquired by Intel Corporation in 2022.

Dave Hughes said: “It’s a remarkable coup to have David, a seasoned executive with a wealth of international experience from thriving technology companies and global industrial giants, join our team. As we embark on the next phase of growth and secure contracts across the UK, Europe, and North America, having David on board in Scotland, the birthplace of ultrasound, is invaluable. His guidance will shape our strategy and operations for continued success.”

Notes:

1. On 22nd June, Novosound CEO Dave Hughes will join Dr. Josef Schmid, a NASA flight surgeon, major general, and mobilization assistant to the surgeon general fo the Air Force, at a Pumps & Pipes event in Houston in collaboration with NASA Tech Talks to discuss launching thin-film ultrasound technologies from energy applications into the aerospace, health, and medtech sectors.
2. In 2022, Novosound secured its latest investment led by Par Equity, supported by Foresight Group (via the Foresight Williams Technology EIS Fund), Kelvin Capital, and Scottish Enterprise.

Contacts

Nick Freer
Freer Consultancy
nick@freerconsultancy.com

What is a personalized Sleep Analysis from Welltory?

Welltory’s Sleep Analysis is a new feature that shows what impacts your sleep, gives you tips to rest better, and tracks 3 science-backed sleep metrics – your Timing, Efficiency, and Recovery. Based on deep heart rate pattern analytics and a personalized approach, this feature is insightful, actionable, and truly unique.

‘Our Sleep Analysis is uniquely insightful because it combines what Welltory does best – deep heartbeat analytics and a personalized approach that adapts each insight to you and your body, helping to steer you toward healthier living’.

Jane Smorodnikova Co-founder and CPO at Welltory

Popular sleep trackers like Oura already recognize the impact of overnight heart rate patterns on recovery, but analyzing patterns accurately requires tons of data. “Thanks to our extensive dataset, we were able to incorporate heart rate patterns into our Recovery score – an innovative metric not just for our app, but for the science of sleep as a whole. We also personalize our analysis to steer you toward better rest. For example, we compare your resting heart rate to your typical overnight heart rate values to better gauge your Recovery score. And your timing score is based not only on how long you slept, but how this compares to your typical sleep duration and usual bedtime”, adds Jane Smorodnikova.

About Welltory

The Welltory App is one of the most reputed health tracking apps. With over 3.5 million users in more than 136 countries and over 50 000 5-star reviews.Up till this day, we have raised $5M investments. Welltory has more than 350k MAU and 30 000 active subscribers, half of them using our app with their Apple Watch. Arizona State University and University College London have used the Welltory App as a scientific research tool. It has been featured as ‘App of the day’ by Apple and is well-reputed through Techcrunch, Men’s Health.

Available in the UK, priced £499.95, ScanWatch Horizon is reminiscent of the Withings Activité – the device that launched the genre in 2014, arriving ahead of the first Apple Watch. Then as now, Withings has opted for a unique analogue face design but with the addition of features expected of a high-end diving timepiece. These include a stainless-steel rotating bezel with laser engraved markings that incorporate the standard codes of diving practice and Luminova hollow watch hands, indicators, and thick indices that allow it to be used in low light.

The sapphire-glass casing with anti-reflection coating and titanium finish adds to its luxury feel. It comes with stainless steel wristband for the classic Diver watch look and a more elasticated rubberised wristband for sports usage. In addition, it boasts a 30-day battery life and a 10 ATM water resistance, which makes it the perfect accessory for swimming, snorkelling, and water sports, which can be monitored using its sport tech features and the connected Health Mate app.

ScanWatch Horizon will get your heart racing and take your breath away with its stunning design yet can detect the disturbances and physiological effects with its medical-grade sensors,” quipped Mathieu Letombe, CEO of Withings. Our core mission is to create beautiful devices people choose to use and wear every day so the clinical data they provide can make meaningful impacts on their lives. Diver watches were created in the 1920s to give navy personnel an underwater timepiece for accuracy during manoeuvres. In the 1950’s SCUBA divers and enthusiasts made them fashionable for any occasion. Now enthused with advanced medical capabilities, Withings aims to bring connected health timepieces to even more users.

Like the original and Rose Gold ScanWatch models, ScanWatch Horizon was developed with medical experts and validated in three clinical trials. It offers extensive and advanced health and fitness capabilities.

In-depth Cardiovascular Health Monitoring

AFib is the main form of irregular heart rhythm that is often underdiagnosed as it can be intermittent and easily missed if symptoms do not occur during infrequent doctors’ visits. ScanWatch can detect if a user has AFib thanks to its ability to take a medical-grade ECG on-demand. ScanWatch also enables users to identify if their heart rhythm is slow, high, or shows signs of AFib through a proactive heart scanning feature. The device can monitor heart rate through its embedded PPG sensor, alerting the user to a potential heart event even if they don’t feel palpitations. ScanWatch then prompts the user to record an ECG in just 30 seconds via the watch display.

Breathing Disturbances Detection

One billion people are estimated to suffer from mild to severe sleep apnea. However, 8 out of 10 people don’t know they have it. ScanWatch can detect the presence of nighttime breathing disturbances (a sign of sleep apnea) with an exclusive algorithm that analyses blood oxygen levels, heart rate, movement, and breathing frequency, collected through ScanWatch’s accelerometer and optical sensors.

In addition, ScanWatch provides sophisticated sleep monitoring and analysis of sleep patterns, including the length, depth, and quality of sleep, and can wake users up with a gentle vibration at the best time of their sleep cycle.

Activity & Workout Tracking

ScanWatch is a sophisticated activity monitor able to track parameters such as steps, calories, elevation, workout routes (via in-app connected GPS) and can automatically recognize more than 30 daily activities such as walking, running, swimming, and cycling. In addition, it offers Fitness Level assessments through estimation of VO2 Max, which measures the heart and muscle’s ability to convert oxygen into energy during physical exercise.

Like all Withings devices, ScanWatch connects with the free Health Mate app, which provides data and insights and the ability to schedule activity reminders, set goals, and manage achievements. In addition, health Mate can be paired with more than 100 third-party apps, including Apple Health, Google Fit, Strava, and MyFitnessPal.

Availability

ScanWatch Horizon will be available in the UK from September, 29th. Priced at €499.95/£499.95. Watch lovers can order online from withings.com and Amazon and choose from either a 43mm screen in Blue or Green. ScanWatch horizon has a 5 year guarantee and comes with both stainless steel wristband and FKM strap.