Identifying critical success factors for wearable medical devices: a comprehensive exploration

Degerli, Mustafa
Yildirim, Sevgi Ozkan
For healthy living, the successful use of wearable medical devices such as smartwatches, smart clothes, smart glasses, sports/activity trackers, and various sensors placed on a body is getting more important as benefits of these devices become apparent. Yet, the existing knowledge about the critical success factors for wearable medical devices needs to evolve and develop further. The main objective of this research is to distill salient constructs to enhance the successful use of wearable medical devices. Specifically, the study aims to identify factors, associated items, and interactions of the relevant factors. A questionnaire has been developed and deployed. The data were collected from 1057 people specifically chosen to represent a wide range of the population. Comprehensive and meaningful inferences have been drawn. Principally, as a fusion of factor analysis and path analysis, a partial least squares structural equation modeling approach consisting of exploratory and confirmatory factor analyses has been applied. In order to assess internal generalization and to precisely identify additional constructs, quasi-statistics have been used. The analyses of data collected revealed 11 salient constructs with 39 items and 18 statistically significant relationships among these constructs. Consequently, composed of distilled constructs and their associations, a novel model with an explanatory power of 73.884% has been approved. Moreover, 13 additional factors were identified as a result of the applied quasi-statistics. This research is the first of its kind on account of its sample characteristics with applied comprehensive methodology and distilled results. This research contributes to the pertinent body of knowledge concerning the critical success factors for wearable medical devices with distilled results. These contributions notably advance the relevant understanding and will be beneficial for researchers and for developers in the field of wearable medical devices.


Exploring the factors affecting consumer intention to use wearable mobile devices to track health information
Pancar, Tansu; Özkan Yıldırım, Sevgi; Department of Information Systems (2021-9)
The popularity and usage of wearable devices is increasing as a consequence of their increasing capabilities. These devices collect various types of health related data with increasing accuracy. Collected data is used by consumers to track their own health data in addition to being used by health professionals to support medical diagnosis and treatment. This research investigates the factors affecting the adoption of wearable devices to track health information. The UTAUT2 model was used as the basis for th...
3-D Rigid Body Tracking Using Vision and Depth Sensors
Gedik, O. Serdar; Alatan, Abdullah Aydın (Institute of Electrical and Electronics Engineers (IEEE), 2013-10-01)
In robotics and augmented reality applications, model-based 3-D tracking of rigid objects is generally required. With the help of accurate pose estimates, it is required to increase reliability and decrease jitter in total. Among many solutions of pose estimation in the literature, pure vision-based 3-D trackers require either manual initializations or offline training stages. On the other hand, trackers relying on pure depth sensors are not suitable for AR applications. An automated 3-D tracking algorithm,...
Cognitive-Node Architecture and a Deployment Strategy for the Future WSNs
Al-Turjman, Fadi (Springer Science and Business Media LLC, 2019-10-01)
The advent of sensing and communication technologies represents the next step in the evolution of wireless sensor networks (WSNs) and future applications. Future WSNs systems demand that connected devices could be able to work autonomously, while surfing on-line generated data and process them for self-decision making. Accordingly, we propose a cognitive Information-Centric Sensor Network (ICSN) framework. The fundamentals of cognition in ICSN can be recognized as a promising direction in addressing opportu...
Classification of motor imagery tasks in EEG signal and its application to a brain-computer interface for controlling assistive environmental devices
Acar, Erman; Gençer, Nevzat Güneri; Department of Electrical and Electronics Engineering (2011)
This study focuses on realization of a Brain Computer Interface (BCI)for the paralyzed to control assistive environmental devices. For this purpose, different motor imagery tasks are classified using different signal processing methods. Specifically, band-pass filtering, Laplacian filtering, and common average reference (CAR) filtering areused to enhance the EEG signal. For feature extraction; Common Spatial Pattern (CSP), Power Spectral Density (PSD), and Principal Component Analysis (PCA) are tested. Line...
Interpreting Group Differences of Relations among Success Factors for Wearable Medical Devices
Özkan Yıldırım, Sevgi; Değerli, Mustafa (2020-10-12)
Currently, wearable technologies are becoming more pervasive and they have several benefits fin- living in a healthy manner. In this context, the critical success factors for wearables are important. However, the existing understanding in this field needs enhancements. In our previous relevant work on the subject of success factors for wearable medical devices, we already distilled the salient factors and meaningful relationships among these factors. On the other hand, to draw additional conclusions, we rec...
Citation Formats
M. Degerli and S. O. Yildirim, “Identifying critical success factors for wearable medical devices: a comprehensive exploration,” UNIVERSAL ACCESS IN THE INFORMATION SOCIETY, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: