Research Article
Effects of a Single Session of Repetitive Transcranial Stimulation in Parkinson Disease
Issue:
Volume 9, Issue 2, June 2024
Pages:
13-20
Received:
24 June 2024
Accepted:
12 July 2024
Published:
23 July 2024
Abstract: Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique proposed for recovery of gait and balance in patients with Parkinson's disease (PD). Our aim was to evaluate the effects of rTMS in PD patients by clinical evaluation and computerized gait analysis. Ten patients were recruited. Each patient was assessed before and after a single session of rTMS by: Berg Scale, Unified Parkinson Disease Rating Scale (UPDRS), 6 Minute Walking Test (6MWT), 10MWT, Time Up and Go (TUG) and spatial-temporal gait analysis by Pablo Gait Assessment sensor. We availed of STM 9000, stimulating with 2000 pulses of 20 Hz rTMS, delivered in 5-second trains with 25 seconds between trains, on the hand area of the motor cortex at 90% resting motor threshold (RMT) on each hemisphere, with 5 minutes pause between hemispheres. Eighty percent of the patient reported subjective benefits, corroborated by objective examination of the results. A significant improvement on the Berg scale was observed. Moreover, a tendence to a significant decrease of stiffness at the lower limbs was evident at UPDRS. Gait analysis showed not significant improvements of evaluated parameters. Although it is premature to draw conclusions, because of the small number of patients, underwent to a single session of rTMS, we confirm the possible beneficial effects and the safety of rTMS. Further studies are needed to validate our findings by clinical evaluation and gait analysis at short, medium, and long term. These may be different in relation to the age, duration and stage of the disease, prevalence of tremor or akinesia and rigidity.
Abstract: Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique proposed for recovery of gait and balance in patients with Parkinson's disease (PD). Our aim was to evaluate the effects of rTMS in PD patients by clinical evaluation and computerized gait analysis. Ten patients were recruited. Each patient was assessed before and after...
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Review Article
Use of AI in Pediatric Occupational Therapy: A Review
Nirvi Sharma*
Issue:
Volume 9, Issue 2, June 2024
Pages:
21-26
Received:
30 May 2024
Accepted:
14 June 2024
Published:
11 September 2024
Abstract: The utilization of artificial intelligence (AI) in pediatric occupational therapy (OT) has emerged as a promising avenue for enhancing assessment, intervention, and outcomes for children with diverse developmental needs. This paper provides a comprehensive review of the current state of AI applications in pediatric OT, highlighting key findings, benefits, challenges, and future directions. AI technologies, including machine learning algorithms, computer vision systems, and wearable sensors, offer innovative approaches to assess children's motor skills, sensory responses, and cognitive functions objectively and efficiently. AI-driven intervention strategies, such as personalized treatment planning, adaptive task selection, virtual reality environments, and gamified activities, promote engagement, motivation, and skill acquisition among pediatric patients. AI can be helpful in early diagnosis as well as early intervention. Additionally, AI-powered telehealth platforms enable remote delivery of OT services, real-time monitoring of patient progress, and access to care for underserved populations. However, challenges related to data privacy, ethical decision-making, disparities in access, and therapist education must be addressed to ensure the ethical, effective, and equitable integration of AI into pediatric OT practice. By embracing ongoing research, collaboration, and innovation, pediatric OT practitioners can harness the transformative potential of AI to improve outcomes and quality of life for children and families worldwide.
Abstract: The utilization of artificial intelligence (AI) in pediatric occupational therapy (OT) has emerged as a promising avenue for enhancing assessment, intervention, and outcomes for children with diverse developmental needs. This paper provides a comprehensive review of the current state of AI applications in pediatric OT, highlighting key findings, be...
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