Search Results (3)

The blood oxygen saturation, which indicates the ratio of oxygenated hemoglobin to total hemoglobin in the blood, is closely related to one’s health status. Oxygen saturation is typically measured using a pulse oximeter. However, this method can cause skin irritation, and in situations where there is a risk of infectious diseases, the use of such contact-based oxygen saturation measurement devices can increase the risk of infection. Therefore, recently, methods for estimating oxygen saturation using facial or hand images have been proposed. In this paper, we propose a method for estimating oxygen saturation from facial images based on a convolutional neural network (CNN). Particularly, instead of arbitrarily calculating the AC and DC components, which are essential for measuring oxygen saturation, we directly utilized signals obtained from facial images to train the model and predict oxygen saturation. Moreover, to account for the time-consuming nature of accurately measuring oxygen saturation, we diversified the model inputs. As a result, for inputs of 10 s, the Pearson correlation coefficient was calculated as 0.570, the mean absolute error was 1.755%, the root mean square error was 2.284%, and the intraclass correlation coefficient was 0.574. For inputs of 20 s, these metrics were calculated as 0.630, 1.720%, 2.219%, and 0.681, respectively. For inputs of 30 s, they were calculated as 0.663, 2.142%, 2.612%, and 0.646, respectively. This confirms that it is possible to estimate oxygen saturation without calculating the AC and DC components, which heavily influence the prediction results. Furthermore, we analyzed how the trained model predicted oxygen saturation through ‘SHapley Additive exPlanations’ and found significant variations in the feature contributions among participants. This indicates that, for more accurate predictions of oxygen saturation, it may be necessary to individually select appropriate color channels for each participant. Full article

Lumbar disc herniation associated with radiculopathy (LDHR) is among the most frequent causes of spine-related disorders. This condition is triggered by irritation of the nerve root caused by a herniated disc. Many non-surgical and surgical approaches are available for managing this prevalent disorder. Non-surgical treatment approaches are considered the preferred initial management methods as they are proven to be efficient in reducing both pain and disability in the absence of any red flags. The methodology employed in this review involves an extensive exploration of recent clinical research, focusing on various non-surgical approaches for LDHR. By exploring the effectiveness and patient-related outcomes of various conservative approaches, including physical therapy modalities and alternative therapies, therapists gain valuable insights that can inform clinical decision-making, ultimately contributing to enhanced patient care and improved outcomes in the treatment of LDHR. The objective of this article is to introduce advanced and new treatment techniques, supplementing existing knowledge on various conservative treatments. It provides a comprehensive overview of the current therapeutic landscape, thereby suggesting pathways for future research to fill the gaps in knowledge. Specific to our detailed review, we identified the following interventions to yield moderate evidence (Level B) of effectiveness for the conservative treatment of LDHR: patient education and self-management, McKenzie method, mobilization and manipulation, exercise therapy, traction (short-term outcomes), neural mobilization, and epidural injections. Two interventions were identified to have weak evidence of effectiveness (Level C): traction for long-term outcomes and dry needling. Three interventions were identified to have conflicting or no evidence (Level D) of effectiveness: electro-diagnostic-based management, laser and ultrasound, and electrotherapy. Full article

The knowledge of the COVID-19 symptomatology has increased since the beginning of the SARS-CoV-2 pandemic. The symptoms of nervous system involvement have been observed across the spectrum of COVID-19 severity. Reports describing difficulties of nerve roots are rare; the affection of brain and spinal cord by SARS-CoV-2 is of leading interest. Our aim therefore is to describe the radicular pain deterioration in the group of nine chronic lumbosacral radicular syndrome sufferers in acute COVID-19. The intensity of radicular pain was evaluated by the Visual Analogue Scale (VAS). The VAS score in acute infection increased from 5.6 ± 1.1 to 8.0 ± 1.3 (Cohen’s d = 1.99) over the course of COVID-19, indicating dramatic aggravation of pain intensity. However, the VAS score decreased spontaneously to pre-infection levels after 4 weeks of COVID-19 recovery (5.8 ± 1.1). The acute SARS-CoV-2 infection worsened the pre-existing neural root irritation symptomatology, which may be ascribed to SARS-CoV-2 radiculitis of neural roots already compressed by the previous disc herniation. These findings based on clinical observations indicate that the neurotropism of novel coronavirus infection can play an important role in the neural root irritation symptomatology deterioration in patients with chronic pre-existing lumbosacral radicular syndrome. Full article