Alterations in gait patterns often indicate health status, and their analysis enables the diagnosis and assessment of various health conditions. This study aimed to develop a noncontact gait analysis system using red, green, and blue-depth (RGB-D) cameras and to evaluate its potential clinical applicability. A single case study was conducted to assess changes in the gait patterns of a patient with stroke before and after the application of an ankle-foot orthosis. Twenty walking trials were recorded to evaluate the key gait parameters. The custom RGB-D camera-based gait analysis system demonstrated the potential to rapidly quantify key gait parameters in the patient. Compared with normative data, it effectively identified characteristic stroke-related gait impairments such as shorter step lengths and slower gait speeds. However, the intraclass correlation coefficient analysis indicated low measurement reliability. Although the stance time and minimum knee angle on the left and right sides exceeded the standard error of measurement (SEM), no changes exceeded the minimal detectable change (MDC) criteria. Moreover, other gait parameters did not show significant changes beyond SEM or MDC, limiting the interpretability of the results. Therefore, further technological developments and data collection are required to improve test-retest reliability and sensitivity to change.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: Tinnitus is a multifactorial condition with no universally accepted assessment guidelines. The Korean Tinnitus Study Group previously established consensus statements on the definition, classification, and diagnostic tests for tinnitus. As a continuation of this effort, this study aims to establish expert consensus on tinnitus assessment and treatment outcome evaluation, specifically tailored to the Korean clinical context. Methods: A modified Delphi method involving 26 otology experts from across Korea was used. A two-round Delphi survey was conducted to evaluate statements related to tinnitus assessment before and after treatment. Statements were rated on a scale of 1 to 9 for the level of agreement. Consensus was defined as ≥ 70% agreement (score of 7–9) and ≤ 15% disagreement (score of 1–3). Statistical measures such as content validity ratio and Kendall’s coefficient of concordance (W) were calculated to assess agreement levels. Results: Of the 46 assessment-related statements, 17 (37%) reached consensus, though overall pre-treatment assessments showed weak agreement (Kendall’s W = 0.319). Key areas of agreement included the use of the visual analogue scale, numeric rating scale, and validated questionnaires for pre-treatment evaluation. Five statements, such as the use of computed tomography, magnetic resonance imaging, and angiography for diagnosing pulsatile tinnitus, achieved over 90% agreement. For treatment outcome measurements, 8 of 12 statements (67%) reached a consensus, with moderate agreement (Kendall’s W = 0.513). Validated questionnaires and psychoacoustic tests were recommended for evaluating treatment effects within 12 weeks. While standardized imaging for pulsatile tinnitus and additional clinical tests were strongly recommended, full consensus was not achieved across all imaging modalities. Conclusion This study provides actionable recommendations for tinnitus assessment and treatment evaluation, emphasizing the use of standardized tools and individualized approaches based on patient needs. These findings offer a practical framework to enhance consistency and effectiveness in tinnitus management within Korean clinical settings.

Background: The question of whether large language models (LLMs) possess consciousness has been increasingly debated. Integrated information theory (IIT) offers a quantitative framework for assessing consciousness through a measure of integrated information. Methods: This study applied IIT principles to the architecture of transformer-based LLMs, focusing on causal integration, temporal persistence, and system irreducibility. Ablation experiments on Generative Pretrained Transformer 2 (GPT-2) were performed, selectively removing individual attention heads and measuring changes in perplexity as a behavioral proxy for integrated information to empirically approximate the measure of integrated information. Results: The ablation study of a single attention head produced minimal or negative changes in perplexity in four out of five representative sentences, indicating redundancy or noise. Only one sentence revealed a significant increase in perplexity change (ΔPPL +11.29), reflecting a localized but nonessential contribution. A comparison with biological systems demonstrated that LLMs meet the IIT criterion of differentiation, but fail to meet the criteria of integration, causal closure, and temporal persistence. These findings confirm that LLMs are architecturally decomposable, lack persistent internal states, and do not sustain global causal irreducibility. Philosophical considerations, including Searle’s Chinese Room argument, further support the idea that the linguistic fluency of LLMs arises from syntactic manipulation rather than semantic understanding. Conclusion Current LLMs do not satisfy the structural and informational requirements of consciousness under IIT. Although capable of simulating intelligent language, LLMs remain unconscious systems with a negligible amount of integrated information, underscoring the distinction between linguistic competence and conscious experience.

A noncontact sensor field is an innovative device that can detect, measure, or monitor physical properties or conditions without direct physical contact with the subject or object under examination. These sensors use a variety of methods, including electromagnetic, optical, and acoustic technique, to collect information about the target without physical interaction. Noncontact sensors find wide-ranging applications in various fields such as manufacturing, robotics, automobiles, security, environmental monitoring, space industry, agriculture, and entertainment. In particular, they are used in the medical field, where they provide continuous monitoring of patient conditions and offer opportunities in rehabilitation medicine. This article introduces the potential of noncontact sensors in the field of rehabilitation medicine.

Purpose: The effect of prehabilitation in patients with frailty undergoing colorectal cancer surgery remains controversial. This meta-analysis aimed to assess the impact of prehabilitation before colorectal surgery on the functional outcomes and postoperative complications in patients with frailty undergoing colorectal cancer surgery. Methods: PubMed, EMBASE, Cochrane Library, and Scopus databases were searched for articles published up to November 9, 2022. We included randomized and non-randomized trials in which the effects of prehabilitation in patients with frailty undergoing colorectal cancer surgery were investigated against a control group. Data extracted for our metaanalysis included the 6-minute walk test (6MWT), postoperative incidence of complications (Clavien-Dindo classification ≥IIIa), comprehensive complication index (CCI), and length of stay (LOS) in the hospital. Results: Compared with the control group, we found a significant improvement in the incidence of postoperative complications and shorter LOS in the hospital in the prehabilitation group. However, the 6MWT and CCI results showed no significant differences between the 2 groups. Conclusion Prehabilitation in patients with frailty who underwent colorectal cancer surgery improved the incidence of postoperative complications and LOS in the hospital. Hence, clinicians should consider conducting or recommending prehabilitation exercises prior to colorectal cancer surgery in patients with frailty.

A narrative review was conducted of machine learning applications and research in the field of stroke rehabilitation. The machine learning models commonly used in medical research include random forest, logistic regression, and deep neural networks. Convolutional neural networks (CNNs), a type of deep neural network, are typically used for image analysis.Machine learning has been used in stroke rehabilitation to predict recovery of motor function using a large amount of clinical data as input. Recent studies on predicting motor function have trained CNN models using magnetic resonance images as input data together with clinical data to increase the accuracy of motor function prediction models. Additionally, a model interpreting videofluoroscopic swallowing studies was developed and investigated. In the future, we anticipate that machine learning will be actively used to treat stroke patients, such as predicting the occurrence of depression and the recovery of language, cognitive, and sensory function, as well as prescribing appropriate rehabilitation treatments.

Background: Videofluoroscopic swallowing study (VFSS) is currently considered the gold standard to precisely diagnose and quantitatively investigate dysphagia. However, VFSS interpretation is complex and requires consideration of several factors. Therefore, considering the expected impact on dysphagia management, this study aimed to apply deep learning to detect the presence of penetration or aspiration in VFSS of patients with dysphagia automatically. Methods: The VFSS data of 190 participants with dysphagia were collected. A total of 10 frame images from one swallowing process were selected (five high-peak images and five low-peak images) for the application of deep learning in a VFSS video of a patient with dysphagia. We applied a convolutional neural network (CNN) for deep learning using the Python programming language. For the classification of VFSS findings (normal swallowing, penetration, and aspiration), the classification was determined in both high-peak and lowpeak images. Thereafter, the two classifications determined through high-peak and low-peak images were integrated into a final classification. Results: The area under the curve (AUC) for the validation dataset of the VFSS image for the CNN model was 0.942 for normal findings, 0.878 for penetration, and 1.000 for aspiration. The macro average AUC was 0.940 and micro average AUC was 0.961. Conclusion This study demonstrated that deep learning algorithms, particularly the CNN, could be applied for detecting the presence of penetration and aspiration in VFSS of patients with dysphagia.