Prevalence of Balance Impairment and Factors Associated with Balance among Patients with Stroke. A Cross Sectional Retrospective Case Control Study

Stroke is a major cause of disability worldwide, and balance impairments are common disabling factors in patients with stroke, leading to falls. Thus, the study objectives were as follows: (i) To find the prevalence of balance impairment among patients with stroke. (ii) To find out the factors associated with balance impairment in patients with stroke. This cross-sectional retrospective case control study involved eighty-one post stroke patients with a mean age of 58.36 ± 14.06, recruited from six hospitals, who underwent an assessment of balance, walking speed, depression and isometric strength of the ankle and knee. These patients were later categorized into subjects with good balance (<45) in the Berg balance scale (BBS) and those with poor balance (≥45), as cases and controls, to assess the factors associated with balance impairment using binary logistic regression. The prevalence of balance impairment among patients with stroke was 48.1%. The reduction in power of knee flexors (OR = 0.858), knee extensors (OR = 0.880) and ankle dorsiflexors (OR = 0.820) was found to be significantly associated with balance impairment, along with speed (OR = 1.187 (95% CI = 1.100, 1.280)), depression (OR = 1.331 (95% CI = 1.055–1.679)) and activities of daily living (OR = 0.313 (95% CI = 0.150–0.650)). In summary, around half of the patients with stroke exhibited balance impairments, with females being more prone

RELATIONSHIP BETWEEN THE THIGH ANTHROPOMETRIC MEASUREMENTS WITH ISOKINETIC PERFORMANCE OF KNEE MUSCLES

Background: Strength measurement is an essential component of assessment in rehabilitation. However, there may be many factors that may alter muscle performance, among which anthropometric values play a significant role. Therefore, the objective of this study is to find out the correlation between thigh anthropometric measurements with the knee isokinetic muscle performance. Methods: Eighteen young, healthy male adults, whose mean age was of 21.22 ± 1.39 were included. Anthropometric measurements like height, weight, thigh girth, and femoral length were correlated with isokinetic strength of knee flexor and extensor muscles. The variables collected in isokinetic measurements; used for analysis were peak torque at three angular velocities of 60°/s, 120°/s, and 180°/s. Results: The Pearson correlation between the thigh girth and isokinetic peak torque at angular velocities of 600/s, 1200/s, and 1800/s for knee extensors were, r = 0.52, 0.69 and 0.73 whereas for knee flexors it was r = 0.53, 0.24 and 0.44 respectively which showed moderate to high correlation when the level of significance was kept at 0.05. However, the correlation between the femoral length and isokinetic peak torque at three angular velocities for knee muscles showed a weak positive correlation only. Conclusion: Study results show that there is a moderate to strong positive correlation exists between thigh girth and isokinetic peak torque of knee musculature, whereas there is only a weak correlation exists between femoral length and isokinetic peak torque of knee musculature. Therefore, it reveals that the length of the extremity does not seem to influence the outcome of isokinetic measurement values. In contrast, the girth of the muscle can influence the outcome of the isokinetic measurement values, especially for the knee joint

TRANSCRANIAL LOW FREQUENCY FOCUSED ULTRASOUND (TLFFU) FOR UPPER LIMB REHABILITATION ON PATIENTS WITH STROKE

Upper limb dysfunction is a significant cause of disability after stroke. Previous studies have shown that the application of low frequency focused ultrasound as a brain stimulation technique modulates the function of the primary somatosensory motor cortex by enhancing sensory discriminative tasks, and application on the primary motor cortex provided cortical excitability. Ultrasound has only recently emerged as a non-invasive human neuromodulation technique for its distinct advantages over other electrotherapeutic techniques such as providing superior specificity and penetrability, eventually enhancing cortical plasticity stroke-affected hemisphere to provide post-stroke regains in upper limb functions

INTEGRATION BETWEEN MRI AND PHYSICAL THERAPY TO IMPROVE TREATMENT OF PATIENTS WITH SHOULDER PAIN

Background: Shoulder pain is the second most common musculoskeletal disorder treated by physical therapists. The cause for the shoulder pain is multifactorial. However, a specific diagnosis is crucial in the right management of shoulder dysfunction. Therefore, the aim of this study was to find out the efficacy of integrating the MRI for the accurate diagnosis and impact of this on rendering the effective physical therapy interventions in shoulder dysfunction patients. Methods: A retrospective study conducted on 14 patients who undergone an MRI with a 1.5 T unit MAGNETOM Symphony (Siemens), for their shoulder pain, where the diagnosis might be Muscle tears like, subscapularis, infraspinatus,supraspinatus and teres minor muscles; subacromial or subdeltoid bursitis and labral tears were included. All the subjects were then continued with usual physical therapy treatments for four weeks depending on their diagnosis which includes; advice, stretching, mobilization and strengthening exercises, manual therapy, massage, strapping, and electrotherapy . The outcome measures documented from the case sheet were; Visual Analogue Scale grade and passive range of motion of shoulder external / internal rotation and abduction. Results: Paired t test was used to compare the PROM between pre rehabilitation and post rehabilitation testing and the non parametric test, Mann Whitney U test was used for the comparison of VAS. All patients showed a significant improvement in VAS and PROM of abduction, internal and external rotation following physical therapy (P≤ 0.05). Conclusion: MRI is found to be a reliable method of diagnostic procedure for the shoulder pain and the integration of MRI and physical therapy to treat shoulder dysfunction leads to a better outcome

Physical therapists’ perceptions and attitudes towards artificial intelligence in healthcare and rehabilitation:A qualitative study

Background: Artificial intelligence (AI) is being introduced to rehabilitation practices, and it can optimize the patient's outcome through their ability to design personalized care strategies and interventions. Objectives: To understand the attitudes and perceptions of physical therapy professionals on the use of AI in rehabilitation in regard to treatment planning, diagnosis, outcome prediction, and advantages and disadvantages. Design and Methods: This paper followed an exploratory, qualitative research design. Semi-structured, one-to-one interviews were conducted with participants of different experience levels and specialties in physical therapy. Results were evaluated using thematic analysis. Results: Four themes were identified: (i) perceptions of AI and its applications in healthcare services, (ii) impact on the workforce (iii) considerations around implementing AI within rehabilitation and (iv) AI, and the fast-approaching future. Participants shared views on the potential impact of AI on rehabilitation practices, such as aiding the decision-making process, saving time and effort of both the therapist and patients. Participants have stressed on potential pitfalls that still need to be considered, such as patient data privacy, potential loss of patient-healthcare practitioner relationship, ethical concerns regarding overreliance on these applications and how that might hinder effective patient care. Conclusion: The findings add to the literature about physical therapists' understanding regarding the use of AI in patient care. Several concerns were raised to the adoption of AI, including concerns about patient privacy, and ethical concerns. Based on the study findings, researchers emphasize the importance of establishing guidelines when incorporating AI in rehabilitation to improve the therapist's knowledge and skills

Physical Therapists’ Knowledge and Attitudes Regarding Artificial Intelligence Applications in Health Care and Rehabilitation: Cross-sectional Study

BackgroundThe use of artificial intelligence (AI) in the field of rehabilitation is growing rapidly. Therefore, there is a need to understand how physical therapists (PTs) perceive AI technologies in clinical practice. ObjectiveThis study aimed to investigate the knowledge and attitude of PTs regarding AI applications in rehabilitation based on multiple explanatory factors. MethodsA web-based Google Form survey, which was divided into 4 sections, was used to collect the data. A total of 317 PTs participated voluntarily in the study. ResultsThe PTs’ knowledge about AI applications in rehabilitation was lower than their knowledge about AI in general. We found a statistically significant difference in the PTs’ knowledge regarding AI applications in the rehabilitation field based on sex (odds ratio [OR] 2.43, 95% CI 1.53-3.87; P<.001). In addition, experience (OR 1.79, 95% CI 1.11-2.87; P=.02) and educational qualification (OR 1.68, 95% CI 1.05-2.70; P=.03) were found to be significant predictors of knowledge about AI applications. PTs who work in the nonacademic sector and who had <10 years of experience had positive attitudes regarding AI. ConclusionsAI technologies have been integrated into many physical therapy practices through the automation of clinical tasks. Therefore, PTs are encouraged to take advantage of the widespread development of AI technologies and enrich their knowledge about, and enhance their practice with, AI applications

Facilitators and Barriers of Artificial Intelligence Applications in Rehabilitation: A Mixed-Method Approach

Artificial intelligence (AI) has been used in physical therapy diagnosis and management for various impairments. Physical therapists (PTs) need to be able to utilize the latest innovative treatment techniques to improve the quality of care. The study aimed to describe PTs&rsquo; views on AI and investigate multiple factors as indicators of AI knowledge, attitude, and adoption among PTs. Moreover, the study aimed to identify the barriers to using AI in rehabilitation. Two hundred and thirty-six PTs participated voluntarily in the study. A concurrent mixed-method design was used to document PTs&rsquo; opinions regarding AI deployment in rehabilitation. A self-administered survey consisting of several aspects, including demographic, knowledge, uses, advantages, impacts, and barriers limiting AI utilization in rehabilitation, was used. A total of 63.3% of PTs reported that they had not experienced any kind of AI applications at work. The major factors predicting a higher level of AI knowledge among PTs were being a non-academic worker (OR = 1.77 [95% CI; 1.01 to 3.12], p = 0.04), being a senior PT (OR = 2.44, [95%CI: 1.40 to 4.22], p = 0.002), and having a Master/Doctorate degree (OR = 1.97, [95%CI: 1.11 to 3.50], p = 0.02). However, the cost and resources of AI were the major reported barriers to adopting AI-based technologies. The study highlighted a remarkable dearth of AI knowledge among PTs. AI and advanced knowledge in technology need to be urgently transferred to PTs