ArticleInternational journal of general medicine2025
Optimal Treatment Strategies of AIoT Based Wearable Devices for Stroke Walking in the Rehabilitation Training of Ischemic Stroke Patients: A Real-World Cohort Study Using Propensity-Score Matched Analysis.
Article in International journal of general medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Methodological Considerations in AIoT-Based Stroke Rehabilitation Research [Letter].International journal of general medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate the efficacy of stroke walking wearable devices based on artificial intelligence Internet of Things (AIoT) technology in the rehabilitation training of patients with ischemic stroke (IS). Patients and Methods: A total of 777 patients with IS were recruited and followed up for 6 months. The participants were divided into control (671 cases) and AIoT group (106 cases) according to whether they received AIoT treatment or not. The primary outcomes were Holden walking function grading, lower limb modified Ashworth muscle tone grading, lower limb Brunnstrom grading, joint range of motion, and gait between two groups of patients within 3 days before treatment and 1 month after treatment. Propensity score matching (PSM) analysis was performed based on various factors such as gender, age, and course of illness at admission. Results: There was no significant difference ( Conclusion: AIoT based walking wearable devices for stroke rehabilitation training is feasible and safe with satisfactory therapeutic effects. Moreover, further prospective multicenter trials are warranted before incorporating AIoT into routine rehabilitation training.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.