A sensor array is to distribute roles between sensors to identify and analyze human bio signals by synthesizing various signals. For example, when a user collapses due to shock, we can know the condition by combining changes in heart rate, breathing, screams , blood pressure, etc. Duranta has a total of 3 sensors.

• ECG (electrocardiogram) sensor that detects heartbeat
• Auditory & biological oscillation sensor for respiration and voice detection
• IR (infrared rays) sensor for oxygen saturation detection

It is essential to comprehensively analyze these sensors in order to make bio signals as data which are more accurate and have long-term utility value. It is difficult to secure reliability for various diagnoses with only one single sensor.

It consists of a detection unit that recognizes bio signals through the sensor formed in this way, and a network which converts the detected signal into data and sends it to the analysis terminal. It is made to be connected to a wearable network of VOC which can store, exchange, and analyze bio signal data detected by each sensor.

It uses AHMM's Transition Probability to replace the GMM sound model with a DNN sound model and analyze the sounds of the human body such as snoring, voice, and breathing.

It provides DNN (Deep Neural Network) operation to filter meaningless sounds from the human body and analyze data based on information that is directly related to the user's health. Users can determine whether there is snoring when verifying the operation result in real time using Voice Recognition System through DNN algorithm. It can determine and predict conditions that can cause a user's sleep apnea, and, if necessary, provide an alarm directly from the wearable device and an indirect alarm to dedicated medical staff.

As it becomes more and more important around the world to manage various chronic and acute diseases, the demand for wearable medical devices in healthcare industry is increasing due to the rapid increase in the demand for real-time monitoring diagnosis and long-term health status through POC(point-of-care). Wearable medical devices have been widely supplied to a wide range of applications, from monitoring bio signals to medical diagnosis. They are being developed to measure important biomarkers for disease diagnosis, physiological health monitoring, and evaluation.

A technology to diagnose COVID-19 with only voice detection has already been developed and approved for medical treatment. A clinical trial on about 300 subjects showed an accuracy of 81.2%. In addition, it is becoming possible to diagnose drug use, depression, ADHD, etc. through artificial intelligence analysis of voice. This data analysis can be extended to infectious diseases as well as COVID-19. It can be used for research on adult diseases by synthesizing blood pressure, electrocardiogram, etc.