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PilOT-Measure:一款移动3D深度感应应用程序,用于支持临床医生主导的准确、高效的居家跌倒风险评估。

PilOT-Measure: a mobile 3D depth sensing application to support accurate and efficient clinician-led home-based falls risk assessments.

作者信息

Ibrahim Zear, Money Arthur G, Atwal Anita, Spiliotopoulou Georgia

机构信息

Department of Computer Science, Brunel University London, Uxbridge, UB8 3PH, UK.

Department of Childhood and Social Care, University of East London, London, E15 4LZ, UK.

出版信息

BMC Med Inform Decis Mak. 2025 Sep 24;25(1):332. doi: 10.1186/s12911-025-03149-7.

Abstract

BACKGROUND

An aging global population, coupled with high levels of assistive equipment abandonment, has propelled increases in falls-related injuries at home. Equipment abandonment occurs, in-part, due to inaccurate measurements of the patient's home taken during the falls risk assessment process. There is an urgent need to explore the value of new digital mobile technologies to help clinicians to take more efficient and effective measurements of patient's home, thereby enhancing the efficacy of falls risk assessments and potentially minimising equipment abandonment.

AIM

The aim of this study is to present and evaluate the accuracy and efficiency of PilOT-Measure, a digital mobile 3D depth-sensor-enabled measurement guidance application for use by clinicians carrying out falls risk assessments.

METHODS

Twenty-one trainee and registered Occupational Therapists took part in this repeated-measures, mixed methods study to evaluate measurement accuracy, task completion time, and overall system usability and user perceptions of the application.

RESULTS

For measurement accuracy, PilOT-Measure outperformed current state of the art handheld tape measure and paper-based measurement guidance booklet. For accuracy consistency, the handheld tape measure and booklet was more consistently accurate for six out of 11 cases. However, PilOT-Measure tended to facilitate significantly faster task completion times, suggesting potential task efficiency benefits. In terms of usability, participants favoured PilOT-Measure and saw potential to reduce administrative tasks and support joint decision-making. Concerns about marker placement on reflective surfaces and patient privacy were noted.

CONCLUSIONS

This study highlights the positive role that mobile depth-sensing technologies can potentially play in improving the efficiency and accuracy of falls risk assessments, hence, reducing levels of equipment abandonment and falls related injuries at home. Future work will focus on improving marker placement, measurement accuracy, and accuracy consistency and explore the potential of using PilOT-Measure as a falls risk patient self-assessment tool.

摘要

背景

全球人口老龄化,加上辅助设备的高遗弃率,导致家庭中与跌倒相关的伤害有所增加。设备被遗弃,部分原因是在跌倒风险评估过程中对患者家庭的测量不准确。迫切需要探索新的数字移动技术的价值,以帮助临床医生更高效、有效地测量患者家庭环境,从而提高跌倒风险评估的效果,并可能减少设备遗弃。

目的

本研究的目的是展示和评估PilOT-Measure的准确性和效率,这是一种数字移动3D深度传感器测量指导应用程序,供进行跌倒风险评估的临床医生使用。

方法

21名实习和注册职业治疗师参与了这项重复测量的混合方法研究,以评估测量准确性、任务完成时间、系统整体可用性以及用户对该应用程序的看法。

结果

在测量准确性方面,PilOT-Measure优于当前最先进的手持式卷尺和纸质测量指导手册。在准确性一致性方面,手持式卷尺和手册在11个案例中的6个案例中更具一致性。然而,PilOT-Measure往往能显著加快任务完成时间,显示出潜在的任务效率优势。在可用性方面,参与者更喜欢PilOT-Measure,并认为它有减少行政任务和支持共同决策的潜力。研究也注意到了对反射表面上标记放置和患者隐私的担忧。

结论

本研究强调了移动深度感应技术在提高跌倒风险评估的效率和准确性方面可能发挥的积极作用,从而减少设备遗弃水平和家庭中与跌倒相关的伤害。未来的工作将集中在改进标记放置、测量准确性和准确性一致性,并探索将PilOT-Measure用作跌倒风险患者自我评估工具的潜力。

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