Cited by 47Mobile Health and mHealth ApplicationsInnovative Human-Technology InteractionUsability and User Interface Design

Perceived user preferences and usability evaluation of mainstream wearable devices for health monitoring

Open access
Jia, Yuxi, Wang, Wei, Wen, Dong, Liang, Lizhong, Gao, Li, Lei, Jianbo·2018·PeerJ

Abstract

Background: There are many problems with fitness trackers, such as device usability, which limit their large-scale application, and relevant studies are limited in terms of their sample size and evaluation methods. The purpose of the study was to evaluate the perceived usability of various mainstream fitness trackers on the market, and to learn about user feedback on feature preferences for each device. Methods: Trial use of seven mainstream fitness trackers (two smart watches and five smart wristbands) followed by a survey study were applied. The questionnaire was specifically developed for this study, which included two parts (user preferences and device usability in five dimensions). We recruited users to test the devices for at least 30 days and asked experienced users to provide feedback in order to evaluate each device, including the rating and user preference of each device. Results: We received 388 valid questionnaires, in which users rated their responses on a five-point Likert scale. (1) User preference: the average user satisfaction was 3.50–3.86 (points), and the rating for willingness to buy averaged between 3.36 and 3.59. More users were willing to wear (58.3–81.3%) and purchase (56.8–83.0%) the devices than were not. The top three general feature preferences were daily activity tracking, heart health monitoring, and professional fitness tracking. The top three health-related feature preferences were heart rate monitoring, daily pedometer, and professional fitness tracking. (2) Usability evaluation: product design was rated from 3.57 to 4.00; durability, 3.63–4.26; ease of use, 3.70–3.90; added features, 3.30–3.83; and user-rated accuracy, 3.44–3.78. A significant difference was observed in the rating of product design and durability among the different devices (p< 0.05) score. Conclusions: Users generally had positive subjective intent regarding fitness trackers but were less satisfied with their cost effectiveness. The users preferred health related features such as heart health monitoring, and professional fitness tracking. The rating of most of the current mainstream fitness trackers was fair with some significant differences among the devices. Thus, further improvement is needed.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.7717/peerj.5350

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 25 · Cited by 47

Research works printed but not linked: 3

  1. Bass L Conveners report of CHI’97 Workshop on Wearable Computers 1997 CHI97 Conference on Human Factors in Computer Systems Hyatt Regency Atlanta Hotel Atlanta, Georgia, USA March 22–27 1997 New York Association for Computing Machinery 22 27
  2. CCSInsight Wearables market to be worth $25 billion by 2019 2016 http://www.ccsinsight.com/press/company-news/2332-wearables-market-to-be-worth-25-billion-by-2019-reveals-ccs-insight 1 March 2018
  3. Xie J Zhang L The review and applications of smart and wearable devices China Medical Device Information 2015 20 3 18 23 10.15971/j.cnki.cmdi.2015.03.004 · DOI

Authors
Jia, Y., Wang, W., Wen, D., Liang, L., Gao, L., & Lei, J.
Affiliations
  • Jilin University (CN)
  • Peking University Third Hospital (CN)
  • Guangdong Medical College (CN)
  • Peking University (CN)
Corresponding author
Lei, Jianbo
Venue
PeerJ
Publisher
PeerJ
Published
2018-07-25
Volume
6
Pages
e5350
ISSN
2167-8359 (ISSN-L)
OpenAlex
W2884151886
Cited by
47
References
25
Citations by year
2026: 3 · 2025: 5 · 2024: 10 · 2023: 9 · 2022: 7 · 2021: 3 · 2020: 6 · 2019: 4
FWCI
4.96
Type
journal article
Language
en
Open access
Locations
  • PeerJ (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Natural Science Foundation of China (NSFC) (#81471756 and #81771937)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
Keywords
wearable activity trackers, wearable devices, health monitoring, usability evaluation, user preferences, smartwatches, smart wristband, heart rate monitoring, activity monitoring, pedometers, product design, durability, purchase intention, cost-effectiveness

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review