| Literature DB >> 31853512 |
Junjie Zhang1, Qingning Su2, William G Loudon3, Katherine L Lee4, Jane Luo5, Brent A Dethlefs6, Shengwen Calvin Li7,8.
Abstract
Rising concerns about the short- and long-term detrimental consequences of administration of conventional pharmacopeia are fueling the search for alternative, complementary, personalized, and comprehensive approaches to human healthcare. Qigong, a form of Traditional Chinese Medicine, represents a viable alternative approach. Here, we started with the practical, philosophical, and psychological background of Ki (in Japanese) or Qi (in Chinese) and their relationship to Qigong theory and clinical application. Noting the drawbacks of the current state of Qigong clinic, herein we propose that to manage the unique aspects of the Eastern 'non-linearity' and 'holistic' approach, it needs to be integrated with the Western "linearity" "one-direction" approach. This is done through developing the concepts of "Qigong breathing signatures," which can define our life breathing patterns associated with diseases using machine learning technology. We predict that this can be achieved by establishing an artificial intelligence (AI)-Medicine training camp of databases, which will integrate Qigong-like breathing patterns with different pathologies unique to individuals. Such an integrated connection will allow the AI-Medicine algorithm to identify breathing patterns and guide medical intervention. This unique view of potentially connecting Eastern Medicine and Western Technology can further add a novel insight to our current understanding of both Western and Eastern medicine, thereby establishing a vitality score index (VSI) that can predict the outcomes of lifestyle behaviors and medical conditions.Entities:
Keywords: AI Medicine; AI deep learning; Qigong; breathing signature; holistic care; immune; inflammation; telomerase activity; tissue microenvironment; traditional Chinese medicine (TCM); vitality score index
Year: 2019 PMID: 31853512 PMCID: PMC6919646 DOI: 10.3390/jfmk4040071
Source DB: PubMed Journal: J Funct Morphol Kinesiol ISSN: 2411-5142
Figure 1Development of a vitality score index (VSI), which is the collective strength of more-specialized signature breathing patterns unique for individuals. The VSI is derived from an AI Medicine algorithm that integrates physiology, heartbeat, pulse oximeter, blood pressure, wristwear, cell phone monitor, respiration and speech, lifestyle, diet, exercise, and breathing pattern. Such VSI data management not only assists our understanding of the underlying biological mechanisms of the whole body, but also predicts the outcomes of behaviors and medical treatment. A normal ECG records the electrical activity of the heart ((Electrocardiogram in English, or EKG—Elektro-kardiographie in German)): P wave (Atrial depolarization), PR segment, PR interval, QRS complex (QRS duration, Ventricular depolarization)), QT interval, ST segment, T wave (Ventricular repolarization), and U wave. Best Respiratory Spirometer Lung Exerciser Suppliers. Artificial intelligence in medicine (AI Medicine, AIMed) will change lives in many ways. Already, AI solutions are being deployed and having a significant impact on healthcare. (Credits: All images belong to Google images. AIMed logo designer: Anthony C. Chang, MD, MPH, MBA, at CHOC Children’s Hospital).
Artificial intelligence-integrated health management of breathing patterns and heartbeat/pulse patterns.
| Technology of Medical Measurement | Evidence-Based Wellness and Maintenance | Disease-Centric Parameters of Personalized Strategies | References |
|---|---|---|---|
| Hypoxia | hypoxia-inducible factors (HIFs). | hypoxia-ischemia | [ |
| Local/regional hypoxia | Hippocampus | CA3 pyramidal neurons | [ |
| Whole-body hypoxia | Heart functions | myocardial infarction | [ |
| Breathing patterns | Non-Invasive Stretchable and Wearable Respiratory Rate Sensor for respiration rate | [ | |
| e-Health nasal sensor (consists of a passive and non-invasive single-lead electrocardiogram (ECG) acquisition module and an ECG-derived respiratory (EDR) algorithm in the working prototype of a mobile application) | [ | ||
| Nose breathing vs. mouth breathing (correlations between mouth breathing and cognition show that decreased oxygen saturation during mouth breathing results not only in morphological deformations but also in poor learning outcomes) | [ | ||
| Heartbeat/pulse patterns | Flattening of the flow velocity (pulse) patterns correlates with the local severity of arteriosclerotic disease | [ | |
| Preventive medicine using pulse oximetry screening | [ | ||
| Pulse transit time (PTT) is the time it takes a pulse wave to travel between two arterial sites (R-wave-gated photo-plethysmography (RWPP) as of measurement of PTT as a surrogate for intra-thoracic pressure changes in obstructive sleep apnea) | [ | ||
| Pulse Oximetry Screening for Critical Congenital Heart Defects | [ | ||
| AI-Medicine algorithm | |||
| Algorithm to track changes in cardiorespiratory interactions (heartbeat intervals and respiratory recordings under dynamic breathing patterns) | [ | ||
| Respiratory sinus arrhythmia (RSA) with algorithm for quantifying instantaneous RSA as applied to heartbeat interval and respiratory recordings in order to track changes in cardiorespiratory interactions elicited during meditation, otherwise not evidenced in control resting states) | [ | ||
| Tongue is a critical organ for respiration and speech | [ | ||
| 18 voice features with posttraumatic stress disorder | [ | ||
| Breathing pattern parameters: Peak airway pressure (Pawpeek), mean airway pressure (Pawmean), tidal volume (VT, mL/kg), minute volume (MV), respiratory muscle unloading (peak electricity of diaphragm (EAdipeak), P 0.1, VT/EAdi), clinical outcomes (ICU mortality, duration of ventilation days, ICU stay time, hospital stay time | [ |