Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences

Theoretical and Natural Science

Vol. 6, 03 August 2023

Open Access | Article

Study of physiological and pathological information mining with biological information similarity analysis

Queena Chan 1 , Shuyu Chen 2 , Yutong Shen * 3
1 Shenzhen Foreign Languages School
2 Shenzhen Foreign Languages School
3 Shenzhen Foreign Languages School

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 6, 275-287
Published 03 August 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Queena Chan, Shuyu Chen, Yutong Shen. Study of physiological and pathological information mining with biological information similarity analysis. TNS (2023) Vol. 6: 275-287. DOI: 10.54254/2753-8818/6/20230251.


Chronic diseases, such as sleep apnea and Parkinson's disease, are characterized by insidious onset, complex etiology, slow course, and easy-to-cause other complications, which seriously affect life quality of the patients. Real-time monitoring of biological information can effectively reveal the occurrence and development of chronic diseases. It also helps in aspects of early diagnosis and treating options. In current study, the dynamic change rules of biological signals caused by chronic diseases have been explored, from which one can realize the auxiliary diagnosis and evaluation of these diseases. Attention has been focused on physiological fluctuation and coordination of biological information similarity, including pulse fluctuation detection in patients with sleep apnea and plantar pressure coordination assessment in patients with Parkinson's disease. In the biological similarity study, the heart rate from sleep apnea patients has been recorded two minutes before and after breath pulse. Information of the average plantar pressure from both foot of Parkinson patients has also been recorded and analyzed. Results show that: for sleep apnea patients, their heart rate fluctuation level has significantly reduced. That is because the human body enhances its sympathetic nerve activity to open the airway. The heart rate starts to change periodically, resulting in its fluctuations tending to be consistent. Compared with ordinary people, PD patients have weaker biological information similarities of plantar pressure on one foot. Also, information similarity between left and right feet of PD patients was more diversified. It revealed that the left and right foot plantar pressure fluctuated more and tended to be more consistent together with gait disorder and weakened balance. Such results show that the similarity of biological information can effectively excavate the fluctuation and coordination of physiological signals, and effectively contribute to the recognition and auxiliary diagnosis of chronic diseases. Data mining methods applied here helps to explore the physiological and pathological mechanism of the studied chronic diseases and sheds light on early diagnosis and severity assessment. It becomes more promising to develop algorithms, software, and hardware systems that is helpful for patients and facilitate promotion of human life quality and health cause.


biological similarity analysis, OSA, Parkinson's disease


1. LADO M J, VILA X A, RODRIGUEZ-LINARES L, et al. Detecting Sleep Apnea by Heart Rate Variability Analysis: Assessing the Validity of Databases and Algorithms. Journal of Medical Systems, 2011, 35(4): 473.

2. MENDONCA F, MOSTAFA S S, RAVELO-GARCIA A G, et al. A Review of Obstructive Sleep Apnea Detection Approaches. IEEE J Biomed Health Inform, 2019, 23(2): 825-37.

3. Hengxi Guo: Epidemiology, etiology and pathogenesis of sleep apnea-hypopnea syndrome. Chinese Journal of Medicine, 2003, (01):9-11

4. Yahui Xu, Fengjuan Liu, Lisheng Wang, Research progress on the relationship between obstructive sleep apnea-hypopnea syndrome and cardiovascular diseases. Journal of Clinical Pulmonary Medicine, 2019, 24(07): 1329-32

5. Chaohua Guo: The pathogenesis, effect, diagnosis and treatment of the OSAHS. Shanxi Medical University, 2010.

6. Yuanming Luo, Baiting He, Pathogenesis and Diagnosis of Obstructive Sleep Apnea: Hot Issues. Chinese Journal of Tuberculosis and Respiratory Diseases, 2015, 38(09):643-5

7. GEOVANINI G R, WANG R, WENG J, et al. Elevations in neutrophils with obstructive sleep apnea: The Multi-Ethnic Study of Atherosclerosis (MESA) . International Journal of Cardiology, 2018, 257: 318-23.

8. ABBASI A, GUPTA S S, SABHARWAL N, et al. A comprehensive review of obstructive sleep apnea. Sleep Sci, 2021, 14(2): 142-54.

9. Yanli Liu, Hui Liang, Lijian Luo, Study on the clinical characteristics of obese patients with obstructive sleep apnea hypopnea syndrome. Journal Of China Prescription Drug, 2022, 20(2):142-54

10. Xiaochen Xie, Xilong Zhang, Mao Huang, Correlation between oxygen desaturation rate and daytime sleepiness in patients with severe obstructive sleep apnea syndrome. National Medical Journal of China, 2020, 100(28):2181-5

11. YOUNG T, EVANS L, FINN L, et al. Estimation of the Clinically Diagnosed Proportion of Sleep Apnea Syndrome in Middle-aged Men and Women. Sleep, 1997, 20(9): 705-6.

12. DRAGER L F, TOGEIRO S M, POLOTSKY V Y, et al. Obstructive Sleep Apnea: A Cardiometabolic Risk in Obesity and the Metabolic Syndrome. Journal of the American College of Cardiology, 2013, 62(7): 569-76.

13. O’MAHONY A M, GARVEY J F, MCNICHOLAS W T. Technologic advances in the assessment and management of obstructive sleep apnoea beyond the apnoea-hypopnoea index: a narrative review. Journal of Thoracic Disease, 2020, 12(9): 5020-38.

14. Thomson Reuters, Disease briefing: Parkinson’s disease. Journal of International Pharmaceutical Research, 2015.

15. Feigin V L, Nichols E, Alam T, et al. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology, 2019, 18(5): 459-480.

16. Dorsey E R, Constantinescu R, Thompson J P, et al. Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology, 2007, 68(5): 384-386.

17. Obeso J A, Stamelou M, Goetz C G, et al. Past, present, and future of Parkinson's disease: A special essay on the 200th Anniversary of the Shaking Palsy. Movement Disorders, 2017, 32(9): 1264-1310.

18. Wu S, Liang D, Yang Q, et al. Regularity of heart rate fluctuations analysis in obstructive sleep apnea patients using information-based similarity. Biomedical Signal Processing and Control, 2021, 65: 102370.

19. Huang Y, Chen Y, Zhu H, et al. A liver fibrosis staging method using cross-contrast network. Expert Systems with Applications, 2019, 130: 124-131.

20. Li Wen, Zhengshi Liu, Yunjian Ge. Several methods of wavelet denoising. Journal of Hefei University of Technology. 2002, (02):167-172

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the International Conference on Modern Medicine and Global Health (ICMMGH 2023)
ISBN (Print)
ISBN (Online)
Published Date
03 August 2023
Theoretical and Natural Science
ISSN (Print)
ISSN (Online)
03 August 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated