India – July 7th, 2021: Mobvoi Inc., a leading voice AI and wearable technology company backed by Google and Volkswagen, today launched a new TicWatch with advanced health and wellbeing sensors.
The TicWatch GTH is the first TicWatch and one of a few smartwatches/wearables with skin temperature measurement. It also has a SpO2 sensor for tracking blood oxygen saturation, a key indicator of your overall health.
Furthermore, Mobvoi, in partnership with a team of Carnegie Mellon University (CMU) scientists, announced the development of an affordable wearable device and a companion AI APP (guardian angel app) for detecting COVID-19 from vital signs, symptoms, and demographic information.
The TicWatch GTH is designed to be an affordable device for people all over the world to detect vital signs. The TicWatch GTH will be available on July 7 on Amazon.in for INR 4,799.00 https://www.amazon.in/dp/B08YJFSJXC?th=1
Advanced health tracking, now with skin temperature monitoring, on the TicWatch GTH
- Skin Temperature Monitoring: This is the first TicWatch with skin temperature monitoring.* It provides you with a 24/7 convenient and non-invasive method for checking if you have an above-normal temperature, enabling you to make smarter decisions about your health.
- Blood Oxygen Saturation Detection: The TicWatch GTH includes a 24/7 SpO2 sensor. Blood oxygen saturation is a key indicator of COVID, even before other symptoms were present.
- 24 Hour Heart Rate Monitoring: Track your heart rate all day, every day, with TicPulse.
- Sleep Tracking and Stress Management: Manage your sleep performance and reduce your stress levels with built-in apps, including TicExercise, TicHealth, TicZen, and TicBreathe.
Fitness tracking with 14 Sports Modes and automatic workout detection
The TicWatch GTH enables you to choose from 14 sport modes, including walking, indoor and outdoor running, indoor and outdoor cycling, jump rope, swimming, rowing, freestyle exercise, mountain climbing, gymnastics, soccer, basketball, and yoga. With Mobvoi’s proprietary TicMotion™ technology, the TicWatch GTH is able to automatically identify and distinguish between the most common exercises: walking and running. It automatically detects when you start working out and asks if you’d like to track it. It spares you from having to manually select your workout type.
Above and beyond battery performance
The TicWatch GTH comes with a 260 mAh battery, giving you more than a week of battery life, depending on usage.**
The TicWatch GTH will feature a 2.5D curved glass screen. Its 1.55” color display with a high screen-to-body ratio allows you to see everything clearly at a glance. You can even take it on a swim with a 5 ATM waterproof rating.
The TicWatch GTH will be available starting on July 7th and can be purchased via Amazon for INR 4,799 https://www.amazon.in/dp/B08YJFSJXC?th=1
TicWatch GTH Specs:
|Dimensions (mm)||43.2 x 35.2 x 10.5|
|Watch strap||TPU (interchangeable), 20mm|
|Display||1.55″ TFT (360 x 320 px)|
|Charging time||About 2 hours|
|Sensors||Accelerometer, Heart Rate Monitor, SpO2 Sensor, Low Latency Off-Body Sensor, Skin Temperature Sensor, Respiration Sensor|
|Waterproof rating||Swim, 5ATM|
*Skin temperature monitoring is not intended to diagnose or treat any medical conditions or for any other medical purpose. It is intended to provide information that helps you manage your health. Significant changes in ambient temperature may affect the accuracy of the measurement.
**Battery life varies with use and other factors.
Collaboration with Turing Scholar Professor Raj Reddy and his team of scientists
Mobvoi connected with a team of CMU professors in Pittsburgh and Masters students in India in May 2020 and started working together in July, focusing on research and development for the algorithm that detects if one has COVID-19. They are also developing an app called Guardian Angel that tells you if you need to visit your physician.
“Shutting down an entire country, or state due to an outbreak should no longer be an option.”, said Prof. Raj Reddy, an AI pioneer and recipient of the ACM Turing Award, considered the Nobel Prize of computer science. “By integrating a predictive platform with an affordable wearable device that tracks all primary vital signs, people will now have access to a powerful health monitoring service, with great benefits for the ongoing effort against the COVID-19 pandemic.”
Other members of the CMU research team include Prof. Naveena Yanamala, Praveen Garimella, Prof. Yuvraj Agarwal, Prof. Mayank Goel, and Ram Konduru.
Detecting COVID-19 with the Guardian Angel App
As more information is becoming available on patients during the ongoing pandemic, it is becoming clear that patients’ vital signs and/or symptoms may present uniquely in COVID-19 infection. Specific patterns or changes in respiratory rate, and heart rate variability were observed in critically ill COVID-19 infected patients. This ongoing research will integrate the real-time tracking of one’s wrist’s skin temperature, blood oxygen saturation, heart rate, and respiration rate with a smartphone-based app to predict markers that can inform the likelihood of having an infection due to COVID-19.
“While the initial presentation of COVID and influenza may appear similar, the number, and combination, of vital signs and symptoms can help provide better stratification.”, said Prof. Naveena Yanamala, Principal Data Scientist at WVU School of Medicine and adjunct professor at CMU. Profs. Yanamala and Garimella’s team was instrumental in developing machine learning models for the Guardian Angel App. “We built our machine learning models using a combination of features (vital signs, symptoms, and demographic information) to identify patterns or markers that can accurately distinguish people with COVID infection from other individuals.”
In addition to extracting information via a wearable device, the app can also directly accept user’s input on their symptoms, vital signs, and other information. Using the app, you can get daily updates on whether you might be infected with COVID and therefore should consult a doctor to confirm or get a formal test.
“A key requirement for adoption was to be able to provide accurate, and early detection of Covid biomarkers, while reducing the data requirement from the user or their wearable device to alleviate privacy concerns of sending raw data to the cloud”, said Prof. Yuvraj Agarwal, Associate Professor at Carnegie Mellon University.
The research team says that at this point, the predictive models have been tested on publicly available datasets drawn from anonymized patient and population health data across the United States. The app developed by the CMU team leverages edge processing; on-device machine learning models ensure the user’s data is private and secure. “In the future, we aim to add more information sources to the models. These sources will include other wearables and apps on the phone to provide more physiological and behavioral information,” said Prof. Mayank Goel.
The CMU team hopes to further evolve this framework into a personal health guardian angel powered by vital sign monitoring and personalized analysis.
Part of the research that went into the development of the ML predictive models by Dr. Yanamala is made available online as open access via Medrxiv to benefit the community.
While the Guardian Angel App is not integrated onto the TicWatch GTH, it will be available on the App Store™ and Google Play Store™ for your smartphone.