Evidence map›Paper›PMID 41229937›Full record

ArticleDigital health

Design of an AI-driven home-based pulmonary telerehabilitation system to enhance patient engagement.

Shih-Ying Chien, Han-Chung Hu, Winston Tseng

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shih-Ying ChienDepartment of Industrial Design, Chang Gung University, Taoyuan.ORCID https://orcid.org/0000-0001-9364-1525
Han-Chung HuDepartment of Thoracic Medicine, Chang Gung Memorial Hospital Taoyuan Branch, Taoyuan.
Winston TsengSchool of Public Health, University of California Berkeley, Berkeley, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Pulmonary telerehabilitation (PTR) has emerged as a promising mobile health approach to address post-discharge challenges faced by patients with chronic pulmonary disease (CPD), including limited professional support, physical discomfort, and declining motivation that may compromise adherence and lung function. Challenges exist in traditional hospital-based rehabilitation, constrained by logistics, limited capacity, and accessibility, especially for elderly or mobility-impaired individuals. This study aimed to investigate the feasibility and usability of a novel home-based PTR system (Intelligent Pulmonary Rehabilitation Exercise System (IPRES)), eliciting user experience reported by a cohort of outpatients with relevant respiratory diseases. Methods: This questionnaire-based, quantitative, single-group pretest-posttest pilot study involved 36 post-discharge CPD patients, predominantly at GOLD stage 3, transitioning from hospital-based to home-based pulmonary rehabilitation Results: Participants reported high usability, with a mean SUS score of 78.87 ± 6.32. Qualitative feedback indicated that personalized feedback, collaborative goal-setting, and gamified interactions enhanced engagement and motivation, with participants highlighting improved understanding of exercise goals, increased confidence in self-managing rehabilitation, and enjoyment of interactive training tasks. Conclusion: This pilot study demonstrates that IPRES is feasible and well-received, highlighting usability strengths and engagement factors that can inform future optimization and randomized controlled trials. While medium- and long-term effectiveness requires further evaluation, these findings support the potential of IPRES as a scalable, patient-centered tool for home-based pulmonary rehabilitation.

Indexed as

AI-driven systembehavior changedigital interventionhome-based rehabilitationmHealthpatient engagementpulmonary telerehabilitationusability

Identifiers

PMID41229937
PMCPMC12602929

What OpenQuestion holds

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Registered trials

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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.