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In this study, it was aimed to reveal the results of posture measurement evaluated by artificial intelligence method, pain status and musculoskeletal disorders in individuals who have had COVID-19.
Thanks to artificial intelligence and machine learning technology, evaluations such as balance and foot pressure measurement can be made in patients today, as well as applications such as exercise and patient follow-up in rehabilitation, solutions to biomedical problems can be offered. Artificial intelligence and machine learning will continue to play an important role in education, training, patient care and research in the future. On the other hand, although various psychological and physical problems have been shown in individuals who have had COVID-19 during the prolonged COVID-19 pandemic process, musculoskeletal disorders and posture problems in these individuals remain unclear. For this reason, in this study, it was aimed to reveal the results of posture measurement evaluated by artificial intelligence method, pain status and musculoskeletal disorders in individuals who have had COVID-19.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Post-COVID-19 group | This group will consist of individuals who have had COVID-19. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Physical evaluations of post-COVID-19 individuals | Other | In this study, pain, posture and musculoskeletal disorders were evaluated in post-COVID-19 individuals. The data to be obtained from all these evaluations were collected from the individuals at one time and over a period of approximately 1 hour at the most. |
| Measure | Description | Time Frame |
|---|---|---|
| Pain Intensity | Pain intensity were measured with the Numerical Rating Scale. This scale expresses the severity of pain with integers from 0 (no pain) to 10 (the worst possible pain). | through study completion, an average of 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Posture assessment | Posture deviation were determined according to the deviation score in the joint centers obtained by photographing the posture of the individuals and uploading them to the system. Posture assessment were made with a mobile application based on the concept of postural analysis with artificial intelligence. | through study completion, an average of 1 year |
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Inclusion Criteria:
Exclusion Criteria:
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41 individuals with post-COVID-19 were included in the research group.
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| Name | Affiliation | Role |
|---|---|---|
| GÜLŞAH BARĞI, Assoc. Dr. | Izmir Democracy University | Study Director |
| HELİN ÖNCEL | Göztepe Sports Club | Principal Investigator |
| SİBEL DENİZ | Izmir Democracy University | Principal Investigator |
| SARA MOHAMMADNEJADIAN | Izmir Democracy University | Principal Investigator |
| MERVE NUR YÜKSEL | Izmir Democracy University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Izmir Democracy University | Izmir | 35140 | Turkey (Türkiye) |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34103818 | Background | Ahuja V, Nair LV. Artificial Intelligence and technology in COVID Era: A narrative review. J Anaesthesiol Clin Pharmacol. 2021 Jan-Mar;37(1):28-34. doi: 10.4103/joacp.JOACP_558_20. Epub 2021 Apr 10. | |
| 35576560 | Background | Itoh N, Mishima H, Yoshida Y, Yoshida M, Oka H, Matsudaira K. Evaluation of the Effect of Patient Education and Strengthening Exercise Therapy Using a Mobile Messaging App on Work Productivity in Japanese Patients With Chronic Low Back Pain: Open-Label, Randomized, Parallel-Group Trial. JMIR Mhealth Uhealth. 2022 May 16;10(5):e35867. doi: 10.2196/35867. |
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| ID | Term |
|---|---|
| D010146 | Pain |
| ID | Term |
|---|---|
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| Score of musculoskeletal disorders | The score of musculoskeletal disorders were evaluated using Cornell Musculoskeletal Disorders Questionnaire.A minimum of 0 and a maximum of 90 points are obtained from the scale for each body area. The total score is obtained by adding the scores for each body area. A high total score indicates that the discomfort in the musculoskeletal system is high. | through study completion, an average of 1 year |