| Selected Publications： |
◆Lin, Y. C., Lin, Y. H., Lo, M Z., Peng, C. K., Huang, N. E., Yang, C. C. H. and Kuo, T. B. J.* (2016) Novel application of multi dynamic trend analysis as a sensitive tool for detecting the effects of aging and congestive heart failure on heart rate variability. Chaos 26:023109
◆Kuo, T. B. J.†, Li, J. Y.†, Kuo, H. K., Chern, C. M. and Yang, C. C. H.* (2016) Differential changes and interactions of autonomic functioning and sleep architecture before and after 50 years of age. Age 38:5 †:co-first
◆Lin, Y. H., Lin, Y. C., Lee, Y. H., Lin, P. H., Lin, S. H., Chang, L. R., Tseng, H. W., Yen, L. Y., Yang, C. C. H. and Kuo, T. B. J.* (2015) Time distortion associated with smartphone addiction: identifying smartphone addiction via a mobile application (App) Journal of Psychiatry Research 65:139-145
◆Kuo, T. B. J. †, Hong, C. H.†, Hsieh, I. T., Lee, G. S. and Yang C. C. H.* (2014) Effects of cold exposure on autonomic changes during the last REM sleep transition and morning blood pressure surge in humans. Sleep Medicine 15:986-97 †:co-first
◆Kuo, T. B. J., Chen, C. Y., Hsu, Y. C. and Yang, C. C. H.* (2012) Performance of the frequency domain indices with respect to sleep staging. Clinical Neurophysiology 123:1338-1345
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| Abstract： |
Application of medical IoT in sleep research
Terry B. J. Kuo, Cheryl C. H. Yang, Yu-Cheng Lin, Jia-Yi Li, Chun-Ting Lai, Cheng-Han Wu
Institute of Brain Science and Sleep Research Center, National Yang-Ming University, Taipei, Taiwan
Internet of things (IoT) is the internetworking of various hardware and network connectivity that enable these objects to collect and exchange data. These include everyday objects such as cell phones, tablets, and machines such as vehicles, monitors and sensors equipped with machine-to-machine connectivity. Polysomnography is a multi-parametric test used in the study of sleep and as a diagnostic tool in sleep medicine. An application of IoT technology in sleep research has a potential to increase the accessibility of the sleep medicine as well as to reduce the overall cost, since the data collection can be done at home and data analysis can be done in the web server. However, great efforts would be taken to accomplish the related hardware designs, algorithm developments, and clinical validations.
With regard to hardware designs, the sensors would be wearable and with the machine-to-machine connectivity. Our laboratory has developed several wearable devices that are capable of recording electrocardiogram, acceleration, chest circumference, and oxygen saturation. All signals can be uploaded to a web server automatically via a cell phone or a specially designed router. Our laboratory also develope several algorithms to analyze the autonomic functions from the electrocardiogram, sleep duration and body position form the acceleration, respiration rate from the chest circumference, and oxygen desaturation index from the oxygen saturation. All of the algorithms can be implemented in the devices or in the web server; therefore, a computer-aided sleep analysis can be done at home with the newly designed wearable devices. Finally, parts of the hardware and algorithm have been validated by the standard polysomnography and sleep scoring system. Broader clinical validations and applications are now ready to launch.
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