Vital Signs Monitor - Built on Science

Vital Signs Monitor – Built on Science

The Science is Conclusive
PPG + AI = Vital Signs Monitor

There is a need for change - for a less expensive vital signs monitor, and better treatments for chronic health conditions, for guiding employee wellness programs and putting personal health responsibility back into the hands of the user with an easy-to-use vital signs monitor - the tools are ready today!

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Keep it Simple, Stupid!
Use Everyday Devices

By using the most ubiquitous device - the smartphone
RE.DOCTOR uses the KISS principle to put healthcare via a vital signs monitor in everyone's hands, or pockets.

Scientific Papers Considered in Design

Want to see what science says about PPG and AI?

These papers are provided for research and are copyright as indicated.

Chandrasekaran, Vikram. “Measuring Vital Signs Using Smart Phones.” (2010).
Smart phones today have become increasingly popular with the general public for its diverse abilities like navigation, social networking, and multimedia facilities to name a few. These phones are equipped with high end processors, high resolution cameras, built-in sensors like accelerometer, orientation-sensor, light-sensor, and much more. According to comScore survey, 25.3% of US adults use smart phones in their daily lives. Motivated by the capability of smart phones and their extensive usage, I focused on utilizing them for bio-medical applications. In this thesis, I present a new application for a smart phone to quantify the vital signs such as heart rate, respiratory rate and blood pressure with the help of its built-in sensors. Using the camera and a microphone, I have shown how the blood pressure and heart rate can be determined for a subject. People sometimes encounter minor situations like fainting or fatal accidents like car crash at unexpected times and places. It would be useful to have a device which can measure all vital signs in such an event. The second part of this thesis demonstrates a new mode of communication for next generation 9-1-1 calls. In this new architecture, the call-taker will be able to control the multimedia elements in the phone from a remote location. This would help the call-taker or first responder to have a better control over the situation. Transmission of the vital signs measured using the smart phone can be a life saver in critical situations. In today's voice oriented 9-1-1 calls, the dispatcher first collects critical information (e.g., location, call-back number) from caller, and assesses the situation. Meanwhile, the dispatchers constantly face a "60-second dilemma"; i.e., within 60 seconds, they need to make a complicated but important decision, whether to dispatch and, if so, what to dispatch. The dispatchers often feel that they lack sufficient information to make a confident dispatch decision. This remote-media-control described in this system will be able to facilitate information acquisition and decision-making in emergency situations within the 60-second response window in 9-1-1 calls using new multimedia technologies

Learn more at Measuring Vital Signs Using Smart Phones

Hoan, Nguyen Van, Jin-Hyeok Park, Suk-Hwan Lee and Ki-Ryong Kwon. “Real-time Hear t Rate Measurement based on Photoplethysmography using Android.” (2017).
With the development of smartphone technologies enable photoplethysmogram (PPG) acquisition by camera and heart rate (HR) measurement. This papers presents improved algorithm to extract HR from PPG signal recorded by smartphone camera and to develop real-time PPG signal processing Android application. 400 video samples recorded by Samsung smartphone camera are imported as input data for further processing and evaluating algorithm on MATLAB. An optimized algorithm is developed and tested on Android platform with different kind of Samsung smartphones. To assess algorithm’s performance, medical device Beurer BC08 is used as reference. According to related works, accuracy parameters includes 90% number of samples that has relative errors less than 5%, Person correlation (r) more than 0.9, and standard estimated error (SEE) less than 5 beats-per-minutes (bpm).

Learn more at Real-time Heart Rate Measurement based on Photoplethysmography

Ong, Ming Chen. “A MOBILE APPLICATION FOR ANXIETY DISORDER TEST USING HRV.” (2017).
Stress are one of the most common issue that are facing by most of the people especially students and also employees. Strong competitive in between human beings are getting more and more significant right now, as number of human beings are increasing every day, while there are limited resources for those who are capable to participate in these intense competition. For anxiety disorder, it is a condition where the patient will be experience this kind of issue where they are persistent and also excessive worry. Anxiety disorders can take in many forms, like fear, stress, panic and etc. But anxiety disorders are treatable and there are number of effective treatments that are already in the medication field. This treatments had already proven that it can resolve the anxiety disorders issue of a patient. The main purpose of this project is to help whoever that need the instant solution to detect and also resolve their anxiety disorder issue like stress at the shortest time, cheapest cost and also convenient for them. This will benefit the user a lot without costing them much. The implementation of this project are using the camera and also the flashlight around the camera to detect the user’s pulse, then determine the HRV from user’s pulse and show their stress level. Moreover, user stress data will also be send back to the server automatically for future reference, and this is to improve the accuracy of the stress data for future development.
Healthcare systems for chronic diseases demand continuous monitoring of physiological parameters or vital signs of the patients’ body. Through these vital signs’ information, healthcare experts attempt to diagnose the behavior of a disease. Identifying the relationship between these vital signs is still a big question for the research community. We have proposed a sophisticated way to identify the affiliations between vital signs of three specific diseases i.e., Sepsis, Sleep Apnea, and Intradialytic Hypotension (IDH) through Pearson statistical correlation analysis. Vital signs data of about 32 patients were taken for analysis. Experimental results show significant affiliations of vital signs of Sepsis and IDH with average correlation coefficient of 0.9 and 0.58, respectively. The stability of the mentioned correlation is about 75% and 90%, respectively.

Learn more at Correlation Analysis of Vital Signs

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