Sensor acceptance model - Measuring patient acceptance of wearable sensors
Sensor acceptance model - Measuring patient acceptance of wearable sensors
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DOI：
10.3414/me9106
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发表时间：
2008-01-01
影响因子：
1.7
通讯作者：
Hejlesen, O.
中科院分区：
文献类型：
--
作者：
Fensli, R.;Pedersen, P. E.;Hejlesen, O.
目的：该项目的重点是患者对可穿戴生物医学传感器的反应，因为患者接受这种监测技术对于提高测量数据的质量至关重要。有一个缺乏有效的问卷调查测量患者接受远程医疗解决方案，和很少的信息是已知的患者如何评估可穿戴sensors.Methods的使用：在信息系统的研究，调查通常用于评估用户满意度的软件程序。基于这一传统，并增加患者满意度和健康相关的生活质量（HRQoL）的措施，传感器接受模型的开发。该模型使用为测量患者对可穿戴传感器的感知接受度而开发的两份调查问卷进行了可操作性。结果：该模型在11名使用新开发的可穿戴心电图传感器的患者中进行了测试，在参考组中有25名患者使用传统的“霍尔特记录仪”。通过验证性因素分析评估结构有效性，并使用克朗巴赫阿尔法系数计算内部一致性。传感器接受指数（SAI）计算为每个病人，显示合理的依赖性和方差scores.Conclusions：本研究试图确定患者的可穿戴传感器的接受，描述了用户接受模型。了解患者的行为和动机代表了设计合适的技术解决方案的一个进步，SAI的计算有望用于比较不同的可穿戴传感器解决方案。然而，这一工具需要更广泛的测试，更广泛的样本量，不同类型的传感器和探索性的后续访谈。
Objectives: This project focuses on how patients respond to wearable biomedical sensors, since patient acceptance of this type of monitoring technology is essential for enhancing the quality of the data being measured. There is a lack of validated questionnaires measuring patient acceptance of telemedical solutions, and little information is known of how patients evaluate the use of wearable sensors.Methods: in information systems research, surveys are commonly used to evaluate the user satisfaction of software programs. Based on this tradition and adding measures of patient satisfaction and health-related quality of life (HRQoL), a Sensor Acceptance Model is developed. The model is made operational using two questionnaires developed for measuring the patients' perceived acceptance of wearable sensors.Results: The model is tested with 11 patients using a newly developed wearable ECG sensor, and with 25 patients in a reference group using a traditional "Holter Recorder". Construct validity is evaluated by confirmatory factor analysis, and internal consistency is calculated using the Cronbach's alpha coefficient. Sensor Acceptance Index (SAI) is calculated for each patient, showing reasonable dependencies and variance in scores.Conclusions: This study attempts to identify patients' acceptance of wearable sensors, describing a user acceptance model. Understanding the patients' behavior and motivation represents a step forward in designing suitable technical solutions, and calculations of SAI can, hopefully, be used to compare different wearable sensor solutions. However, this instrument needs more extensive testing with a broader sample size, with different types of sensors and by explorative follow-up interviews.