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Introduction PSG (Polysomnography) as a traditional instrument for multi-modal monitoring device, has been considered as golden standard for sleep related vital sign monitoring for many decades. But it is sometimes considered burdensome due to its wet EEG electrodes cap, its time-consuming wearing, and it is not suitable for tele-health and at-home monitoring purpose, for chronic disease management especially for elderly senior people. Methods Given this, a nano-electronic based sleep monitoring patch device has been developed to overcome these obstacles. The device implements metallic nano-particle electrodes to increase data acquisition efficiency, and well-developed hydrogel to increase skin biocompatibility and gas permeability. Also, the device integrates EEG chip design and three-electrode based setup, to avoid traditional 8-channel or 16-channel EEG headset and dramatically increase the convenience of usage. In terms of software, the device uses artificial intelligence deep learning network to train sleep staging algorithm and implement advanced data processing technology to differentiate EEG, EOG and EMG from the raw data acquired by the device in the forehead. Results In this way, the device can also detect characteristic waveform such as slow waveform, kappa complex and spindle etc. All these factors result in 85-95% accuracy of sleep staging percentages, as compared to PSG golden standard, which is dramatic. Conclusion The device has passed Class II medical NMPA approval in China and it is getting approval in US FDA very soon. It is believed that this device can be used not only in traditional sleep center and hospital all over the world, but can it also be used in a variety of different departments such as psychiatry, ICU and neurology, as well as rehab centers, nursery, and many other circumstances and locations. It is believed it is beneficial not only for doctors, but for researchers as well. Support (if any)
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Yu Sun (2024) studied this question.
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