Methods Inf Med 2008; 47(01): 89-95
DOI: 10.3414/ME9106
For Discussion
Schattauer GmbH

Sensor Acceptance Model – Measuring Patient Acceptance of Wearable Sensors

R. Fensli
1   University of Agder, Faculty of Engineering and Science, Grimstad, Norway
,
P. E. Pedersen
1   University of Agder, Faculty of Engineering and Science, Grimstad, Norway
,
T. Gundersen
2   Sørlandet Sykehus, HF, Medical Department, Arendal, Norway
,
O. Hejlesen
3   Aalborg University, Department of Health Science and Technology, Aalborg, Denmark
› Author Affiliations
Further Information

Publication History

Publication Date:
19 January 2018 (online)

Summary

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.

 
  • References

  • 1 Lukowicz P, Kirstein T, Tröster G. Wearable systems for health care applications. Methods Inf Med 2004; 43 (03) 232-238.
  • 2 Maglaveras N, Chouvarda I, Koutkias V, Meletiadis S, Haris K, Balas EA. Information Technology Can Enhance Quality in Regional Health Delivery. Methods Inf Med 2002; 41 (05) 393-400.
  • 3 Fensli R, Gunnarson E, Gundersen T. A wearable ECG-recording system for continuous arrhythmia monitoring in a wireless tele-home-care situation. Proceedings 18th IEEE Symposium on Computer- Based Medical Systems; 2005 June 23-24; Dublin; Ireland: 2005. pp 407-12.
  • 4 Anliker U, Ward JA, Lukowicz P, Troster G, Dolveck F, Baer M. et al. AMON: a wearable multiparameter medical monitoring and alert system. Information Technology in Biomedicine, IEEE Transactions on. 2004; 8 (04) 415-427.
  • 5 Knight JF, Schwirtz A, Psomadelis F, Baber C, Bristow HW, Arvanitis TN. The design of the SensVest. Personal and Ubiquitous Computing. 2005; V9 (01) 6-19.
  • 6 Lindholm C, Keinonen T, Kiljander H. Mobile usability: How Nokia Changed the Face of the Mobile Phone. McGraw-Hill; 2003
  • 7 Sharp H, Rogers Y, Preece J. Interaction Design: Beyond Human Computer Interaction. John Wiley & Sons; 2007
  • 8 Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly. 1989; 13 (03) 319-340.
  • 9 Venkatesh V, Morris MG, Davis GB, Davis FD. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. 2003; 27 (03) 425-478.
  • 10 Mair F, Whitten P. Systematic review of studies of patient satisfaction with telemedicine. BMJ. 2000 June 3, 2000; 320 7248 1517-1520.
  • 11 Williams TL, May CR, Esmail A. Limitations of Patient Satisfaction Studies in Telehealthcare: A Systematic Review of the Literature. Telemedicine Journal and e-Health 2001; 7 (04) 293-316.
  • 12 Lehoux P. Patients’ Perspectives on High-Tech Home Care: A Qualitative Inquiry into the User- Friendliness of Four Interventions. BMC Health Services Research. 2004; 4: 28.
  • 13 Heinzelmann PJ, Williams CM, Lugn NE, Kvedar JC. Clinical Outcomes Associated with Telemedicine/ Telehealth. Telemedicine and e-Health 2005; 11 (03) 329-347.
  • 14 Hopp F, Woodbridge P, Subramanian U, Copeland L, Smith D, Lowery J. Outcomes Associated with a Home Care Telehealth Intervention. Telemedicine and e-Health 2006; 12 (03) 297-307.
  • 15 Ware JE, Kosinski M, Dewey JE. How to Score Version 2 of the SF-36® Health Survey. Lincoln, RI: QualityMetric Incorporated; 2000
  • 16 Stofmeel MAM, van Stel HF, van Hemel NM, Grobbee DE. The relevance of health related quality of life in paced patients. International Journal of Cardiology 2005; 102 (03) 377-382.
  • 17 Doll WJ, Xiaodong D, Raghunathan TS, Torkzadeh G, Xia W. The Meaning and Measurements of User Satisfaction: A Multigroup Invariance Analysis of the End-User Computing Satisfaction Instrument. Journal of Management Information Systems 2004; 21 (01) 227-262.
  • 18 Demiris G. Principles of survey development for telemedicine applications. Journal of Telemedicine & Telecare 2006; 12: 111-115.
  • 19 Fensli R, Gundersen T, Gunnarson E. Design Requirements for Long-Time ECG Recordings in a Tele-Home-Care Situation, A Survey Study. Scandinavian Conference in Health Informatics 2004 August 23-25; Arendal, Norway: 2004. pp 14-18.
  • 20 McKinney V, Yoon K, Zahedi FM. The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach. Information Systems Research 2002; 13 (03) 296-315.
  • 21 Fensli R, Gunnarson E, Gundersen T. Design Requirements for Long-Time ECG Recordings in a Tele-Home-Care Situation, A Survey Study. Proceedings Scandinavian Conference in Health Informatics; 2004 August 23-25; Arendal, Norway: 2004. pp 14-18.
  • 22 Nunnally JC. Psychometric Theory. Second Edition. McGraw-Hill; 1978
  • 23 Wireless Patient Recording Medical AS. Wireless ECG sensor. [cited 2007 03.30]; Available from: http://www.wprmedical.com
  • 24 Huntleigh Healthcare.. Medilog AR4 Digital Holter Recorder. [cited 2007 03.30]. Available from: http://www.medilogdarwin.com/Medilog_AR4.html
  • 25 Tabachnick BG, Fidell LS. Using multivariate statistics. 4th ed. NewYork: HarperCollins; 2001
  • 26 Winters JM, Dshalalow JH. Medical Instrumentation: Accessibility and Usability Considerations. CRC Press; 2006
  • 27 Demiris G, Speedie SM, Finkelstein S. Change of Patients’ Perceptions of TeleHomeCare. Telemedicine Journal and e-Health 2001; 7 (03) 241-248.