Clebre
Device for home diagnosis of respiratory disorders
Medical device prototyping and development for the real-time respiratory disorders monitoring and related parameters during sleep.
Challenge
Develop a comfortable device that enables real-time monitoring of breath related parameters during sleep. The device should be ready for clinical trials.
Develop a comfortable device that enables real-time monitoring of breath related parameters during sleep. The device should be ready for clinical trials.
Approach
In the first stage of the project we performed an audit of existing solution and analysis of functional requirements. Then we were able to develop a detailed plan of the project. We divided our work into 3 parts: definition of sound transfer solution and device mechanics, development of prototypes for tests and initial algorithm for sound detection during sleep and production of devices with implemented detection algorithms that are ready for clinical trials.
In the first stage of the project we performed an audit of existing solution and analysis of functional requirements. Then we were able to develop a detailed plan of the project. We divided our work into 3 parts: definition of sound transfer solution and device mechanics, development of prototypes for tests and initial algorithm for sound detection during sleep and production of devices with implemented detection algorithms that are ready for clinical trials.
Outcome
We developed 10 devices that were able to record the signal for the whole night, perform analysis and detect breathing, snoring and apnea. Moreover they were evaluated as comfortable. The devices were ready for clinical tests, which aimed to evaluate the implemented algorithms. The approach involved gathering requirements and testing, learning, building, and testing further, resulting in the development of final prototypes for clinical trials that record signal from 2 acoustic channels and 3 accelerator axes, detect breathing, snoring, apneas, transmit data through BLE, and save audio signal and accelerator data on SD card. The next step is to conduct extensive clinical recordings that will enable the collection of data for the development of the detection system and classification of breathing disorders.
We developed 10 devices that were able to record the signal for the whole night, perform analysis and detect breathing, snoring and apnea. Moreover they were evaluated as comfortable. The devices were ready for clinical tests, which aimed to evaluate the implemented algorithms. The approach involved gathering requirements and testing, learning, building, and testing further, resulting in the development of final prototypes for clinical trials that record signal from 2 acoustic channels and 3 accelerator axes, detect breathing, snoring, apneas, transmit data through BLE, and save audio signal and accelerator data on SD card. The next step is to conduct extensive clinical recordings that will enable the collection of data for the development of the detection system and classification of breathing disorders.
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