Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology

Objective: This study aims to identify unique characteristics of depression based on Gas Discharge Visualization (GDV) technology. Methods: A total of 120 participants with depressive symptoms (Group A) and 56 healthy controls (Group B) were assessed using GDV technology to identify energy value dif...

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Main Authors: Fei Gao, Liangsong Li, Qian Hu
Format: Article
Language:English
Published: Mary Ann Liebert 2024-03-01
Series:Integrative Medicine Reports
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Online Access:https://www.liebertpub.com/doi/10.1089/imr.2024.0021
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author Fei Gao
Liangsong Li
Qian Hu
author_facet Fei Gao
Liangsong Li
Qian Hu
author_sort Fei Gao
collection DOAJ
description Objective: This study aims to identify unique characteristics of depression based on Gas Discharge Visualization (GDV) technology. Methods: A total of 120 participants with depressive symptoms (Group A) and 56 healthy controls (Group B) were assessed using GDV technology to identify energy value differences. Statistical analysis identified specific markers useful in confirming a diagnosis of depression. Results: Group A showed significantly lower energy values than Group B in all systems except the respiratory and urogenital systems (p < 0.05). Conversely, higher energy values were observed in the respiratory system’s throat, larynx, and trachea in Group A (p < 0.05). Within Group A, the lowest energy values were in the head, cardiovascular, and immune systems (p < 0.01), while the highest were in the respiratory and urogenital systems (p < 0.01). In the head, energy values were lower in the eyes (p < 0.05). Within the endocrine system, the thyroid showed the highest energy, and the epiphysis the lowest (p < 0.05). The transverse colon and duodenum exhibited the lowest energy in the digestive system (p < 0.001). The spine-lumbar zone and kidneys showed lower energy in their respective systems (p < 0.001). The throat, larynx, and trachea displayed the highest energy in the respiratory system (p < 0.001). Conclusion: GDV technology can be utilized for the auxiliary diagnosis of depression: Energy values are the lowest in the head, cardiovascular, and immune systems, and highest in the respiratory and urogenital systems. Lower energy values in the eyes within the head, with the thyroid and epiphysis marking the highest and lowest energy values in the endocrine system. The sacrum and the kidneys exhibited lower energy values within their respective systems, the transverse colon and duodenum had the lowest energy values within the digestive system. The throat, larynx, and trachea showed the highest energy values within the respiratory system.
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spelling doaj-art-596c5c00155e4181ac798f46a8dcb8fa2025-08-20T03:49:37ZengMary Ann LiebertIntegrative Medicine Reports2768-32222024-03-013113214410.1089/imr.2024.0021Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization TechnologyFei Gao0Liangsong Li1Qian Hu2School of Chinese Classics, Beijing University of Chinese Medicine, Beijing, China.School of Chinese Classics, Beijing University of Chinese Medicine, Beijing, China.The Fourth People’s Hospital of Liaocheng, Liaocheng, China.Objective: This study aims to identify unique characteristics of depression based on Gas Discharge Visualization (GDV) technology. Methods: A total of 120 participants with depressive symptoms (Group A) and 56 healthy controls (Group B) were assessed using GDV technology to identify energy value differences. Statistical analysis identified specific markers useful in confirming a diagnosis of depression. Results: Group A showed significantly lower energy values than Group B in all systems except the respiratory and urogenital systems (p < 0.05). Conversely, higher energy values were observed in the respiratory system’s throat, larynx, and trachea in Group A (p < 0.05). Within Group A, the lowest energy values were in the head, cardiovascular, and immune systems (p < 0.01), while the highest were in the respiratory and urogenital systems (p < 0.01). In the head, energy values were lower in the eyes (p < 0.05). Within the endocrine system, the thyroid showed the highest energy, and the epiphysis the lowest (p < 0.05). The transverse colon and duodenum exhibited the lowest energy in the digestive system (p < 0.001). The spine-lumbar zone and kidneys showed lower energy in their respective systems (p < 0.001). The throat, larynx, and trachea displayed the highest energy in the respiratory system (p < 0.001). Conclusion: GDV technology can be utilized for the auxiliary diagnosis of depression: Energy values are the lowest in the head, cardiovascular, and immune systems, and highest in the respiratory and urogenital systems. Lower energy values in the eyes within the head, with the thyroid and epiphysis marking the highest and lowest energy values in the endocrine system. The sacrum and the kidneys exhibited lower energy values within their respective systems, the transverse colon and duodenum had the lowest energy values within the digestive system. The throat, larynx, and trachea showed the highest energy values within the respiratory system.https://www.liebertpub.com/doi/10.1089/imr.2024.0021depressiondiagnosisenergygas discharge visualization
spellingShingle Fei Gao
Liangsong Li
Qian Hu
Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology
Integrative Medicine Reports
depression
diagnosis
energy
gas discharge visualization
title Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology
title_full Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology
title_fullStr Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology
title_full_unstemmed Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology
title_short Study on Auxiliary Diagnosis of Depression Based on Gas Discharge Visualization Technology
title_sort study on auxiliary diagnosis of depression based on gas discharge visualization technology
topic depression
diagnosis
energy
gas discharge visualization
url https://www.liebertpub.com/doi/10.1089/imr.2024.0021
work_keys_str_mv AT feigao studyonauxiliarydiagnosisofdepressionbasedongasdischargevisualizationtechnology
AT liangsongli studyonauxiliarydiagnosisofdepressionbasedongasdischargevisualizationtechnology
AT qianhu studyonauxiliarydiagnosisofdepressionbasedongasdischargevisualizationtechnology