Background: Stroke is the leading cause of long-term disability in the world and there is a compelling need for scalable and effective rehabilitation strategies. Combined with the help of artificial intelligence (AI) based pose estimation technologies, telerehabilitation is a promising paradigm for taking evidence-based motor rehabilitation beyond the hospital. But, clinical validity, accuracy benchmarks and patient compliance of such systems are poorly defined.

Objective: This study aimed to systematically review the accuracy of AI-based pose estimation systems, their clinical effectiveness on validated motor and functional outcomes in stroke survivors in the context of telerehabilitation, and the rate of patient adherence.

Methods: A systematic review with PRISMA 2020 guidelines. The six electronic databases (PubMed, Scopus, Web of Science, IEEE Xplore, Embase, and the Cochrane Library) were searched from January 2015 to April 2026, with the specific Boolean search strings defined for each of the six databases. Studies included in the eligible studies recruited adult stroke survivors and used AI pose estimation (OpenPose, MediaPipe, Kinect/Azure Kinect, or similar system) and had at least one quantitative outcome reported. The Cochrane RoB 2 tool, ROBINS-I and Newcastle–Ottawa Scale were used as appropriate for appraising risk of bias.

Results: Twenty-seven studies (1,482 participants) included. The accuracy of the pose estimation was between 78% and 97%, with Azure Kinect and the deep learning pipelines (OpenPose, MediaPipe) achieving a lower joint angle root mean square error (RMSE 2.1°-5.8°) compared to the first generation of Kinect v2 (6.3°-12.4°). The mean change in Fugl-Meyer Assessment (FMA) score across 21 of the 25 reporting studies was 8.3 points (95% CI 6.1–10.5) to improve significantly. Improvements in Berg Balance Scale and Barthel Index scores also were similar. Compliance averaged 78.4% (range 52%–96%), much better than standard therapy compliance rates for conventional outpatient therapy. For the most part, the Technology Usability scores (System Usability Scale) were above 70.

Conclusion: AI-based pose estimation systems show clinical meaningful accuracy and are able to facilitate measurable improvement in motor function, balance and activities of daily living in stroke survivors in telerehabilitation settings. Patients' adherence is comparable to face-to-face therapy. These findings need to be consolidated into clinical practice guidelines through standardisation of accuracy metrics, longitudinal designs and prospective randomised trials.

Abstract

Background: Dental amalgam remains in clinical use as a restorative material despite ongoing concerns about its mercury content. Undergraduate dental students represent a vulnerable occupational group; however, their awareness of mercury-related health hazards and safe handling practices in the Delhi-NCR context remains insufficiently characterised.

Objective: To evaluate awareness of mercury-related health hazards and the mercury hygiene practices adopted by undergraduate dental students in Delhi-NCR during clinical procedures involving amalgam.

Methods: A cross-sectional survey was conducted among 300 undergraduate dental students (second to fourth year BDS and interns) at institutions in the Delhi-NCR region. Data were collected via a 25-item structured online questionnaire. Chi-square tests of independence were applied at the 5% significance level to examine associations between academic year and awareness or practice outcomes.

Results: Overall awareness of mercury in dental materials was 97.0%, yet only 52% of participants demonstrated adequate mercury hygiene knowledge. Statistically significant inter-group differences were observed for curriculum exposure (p = 0.031), identification of mercury vapour as the most hazardous form (p = 0.031), knowledge of the safe biological threshold (p < 0.001), awareness of mercury release during condensation (p = 0.040), current clinical use (p = 0.040), and knowledge of mercury accumulation sites (p = 0.019).

Conclusions: Significant knowledge deficiencies exist across all academic levels. Standardised, competency-based mercury hygiene training must be integrated into undergraduate dental curricula to protect practitioners, patients, and the environment.

Abstract

Background: Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder characterized by recurrent episodes of severe, unilateral facial pain along the distribution of the trigeminal nerve. Owing to its resemblance to odontogenic pain, TN is frequently misdiagnosed, resulting in unnecessary dental interventions and delayed treatment.

Case Presentation: A 20-year-old female reported with severe pain in the upper right posterior maxillary region for three years. The pain persisted despite extraction of the maxillary right third molar and previous pharmacological management. Clinical examination revealed trigger zones over the right cheek and upper lip, with a Visual Analog Scale (VAS) score of 9/10. Based on the patient’s history and characteristic clinical findings, a diagnosis of right-sided trigeminal neuralgia was established.

Management and Outcome: Initial treatment with carbamazepine and pregabalin showed minimal improvement. Subsequently, the treatment regimen was modified to include a higher dose of carbamazepine along with gabapentin, amitriptyline, and methylcobalamin. Following three months of therapy, the patient demonstrated significant symptomatic improvement, with the VAS score decreasing from 9/10 to 4/10 and a marked enhancement in quality of life.

Conclusion: This case highlights the importance of considering trigeminal neuralgia in the differential diagnosis of persistent facial and dental pain, particularly when symptoms persist after dental treatment. Early recognition, identification of trigger zones, and appropriate pharmacological management can lead to substantial pain reduction and improved patient outcomes.