Wearable Technology

Overview

Wearable technologies are devices designed to be worn conveniently on a person’s body and generally serve to reduce the daily demands on an individual. They are relatively discrete, lightweight, and hard to forget or lose. A common example is a wristwatch, though modern wearable technologies can do many more things. Most wearable technologies can be classified as trackers (such as heart rate monitors typically used for exercise), reminders (anything that presents information to the wearer without recording any information, like a watch or timer), or regulators (devices that pick up data and actively send feedback, such as a pressure vest).

The simplest devices gather no information from the body and are variations on timers with notifications, essentially all they do is remind and prompt. It has been shown that these reminder devices are effective in creating behavioral changes in high school students (Frank, Jacobs, & Mcloone, 2017), children who are overweight (Schoeppe et al., 2017), and individuals with developmental disabilities (Naslund, Aschbrenner, & Bartels, 2016). In general, these devices work effectively for prompting a target behavior and are simple to use.

Trackers are relatively familiar, carry minimal disadvantages, and perform as advertised by recording bodily signals or other basic information, such as steps taken, blood pressure, heart rate, or breathing rate (Buntin et al., 2011). A review of 54 different articles on the effectiveness of trackers showed that these trackers increase physical fitness, physical activity, weight loss, and overall health (Strath & Rowley, 2017). The degree of improvement varied across the studies that were reviewed.

Trackers have also been used to recognize emotional states in hopes of providing increased awareness of moods to make emotional regulation easier. In an attempt to better identify anxiety in patients, Katsis, Katertsidis, & Fotiadis (2011) showed a finger-worn monitor could accurately (84% correct) sort patients into one of five levels of increasingly anxious states. This study had the patients remain still during data collection, which led to cleaner, more accurate results but makes it more difficult to generalize to everyday life. A more recent study has shown that anxiety levels can be monitored somewhat accurately (62% correct) during high intensity sporting events; this study used a somewhat more intrusive head cap to measure brain signals (Zheng et al., 2016). Similar to anxiety, trackers have been used with individuals who have autism spectrum disorder, as these individuals typically have difficulty recognizing their own emotional states (McCraty & Zayas, 2014). Koo and colleagues developed a prototype sensory vest which monitored emotional states and was rated favorably by patients tested (Koo et al., 2018). However, this study did not include a control group.  

A relatively new field of technology is the rise of regulating devices, which send signals automatically to the wearer. The deeper neuroscience of these technologies is positive, showing potential regarding the use of electrical signals from devices to affect brain activity (McCraty & Zayas, 2014; Tyler et al., 2015). The effects of electrical signaling technologies such as Thync are mixed, in how strong of an effect, if at all, they create (Tyler et al., 2015). In contrast, strong evidence supports the physical signaling technologies, such as Doppel, which uses vibrations to regulate moods (Azevedo et al., 2017).

While most of recent studies have shown moderate to strongly positive effects for wearable technologies (142 out of 154 studies, or 92% positive effects), there have been some documented concerns with wearable technologies (Buntin et al., 2011). The concerns identified in Buntin’s meta analysis include increased time spent transferring data from devices onto computers, reduced time spent between patient and doctor, and more complicated recordkeeping, including a shift in responsibilities.

Research Rating: Due to the experimental nature of the information cited in this description this information is to be trusted as valid and reliable.  

Advantages:

  • Basic features are rigorously validated in the literature and effective: prompting, reminders

  • Well-documented positive effects for physical health management, including diet and exercise

  • Relatively easy to use, making these techs feasible for individuals with developmental disabilities

  • Solid research base for mood monitoring technology, and the field continues to show improvements

Disadvantages:

  • Devices can be expensive, and there are hundreds of different products on the market to choose from

  • Positive effects may be small

To Consider

There is a lot of positive “buzz” on unregulated opinion sites praising these products. When purchasing, temper expectations and promises made by advertising companies to what has been shown so far in the research literature. Wearable technologies with basic reminder functions are very effective, and health monitoring/fitness apps are also fairly effective. Mood monitoring is less clearly effective but still generally positive, and there is currently not enough information on electrophysiological stimulant technology to determine whether or not they are effective. Physical signals (blood pressure, breathing rate, vibrations) have better evidence than electrical signals (galvanic skin responses, brain waves). Also note these devices, despite showing positive effects, lead to relatively small “boosts”, intended to compliment a plan of action, so they should not be used in absence of other strategies. Finally, because this is such a new field, new information is constantly being discovered.

Exact prices change frequently, which is why only approximate ranges are listed. 

$ - Under $5

$$ - Between $6 and $50

$$$ - Between $51 and $250

$$$$ - Over $250

References

 

Bottos, M., Bolcati, C., Sciuto, L., Ruggeri, C., & Feliciangeli, A. (2001). Powered wheelchairs and independence in young children with tetraplegia. Developmental Medicine & Child Neurology, 43, 769-777.

 

Greer, N., Brasure, M., & Wilt, T. J. (2012). Wheeled mobility (wheelchair) service delivery: Scope of the evidence. Annals of Internal Medicine, 156, 141-146.

 

Marchiori, C., Bensmail, D., Gagnon, D., & Pradon, D. (2015). Manual wheelchair satisfaction among long-term users and caregivers: A French study. JRRD, 52, 181-191.  

 

Reid, D., Laliberte-Rudman, D., & Hebert, D. (2002). Impact of wheeled seated mobility devices on adult users’ and their caregivers’ occupational performance: A critical literature review. The Canadian Journal of Occupational Therapy, 69, 261-280.

 

Rodby-Bousquet, E., Paleg, G., Casey, J., Wizert, A., & Livingstone, R. (2016). Physical risk factors influencing wheeled mobility in children with cerebral palsy: A cross-sectional study. BMC Pediatrics, 16, 395-406.

 

Taylor, S., et al. (2015). Patterns in wheeled mobility skills training, equipment evaluation, and utilization: Findings from the SCIRehab project. Assistive Technology, 27, 59-68.

 


 

Written by Bronwyn Lamond, Last Revision May 2018

Academic Intervention Lab

Department of Applied Psychology and Human Development

Ontario Institute for Studies in Education, Toronto, ON M5S 1V6, Canada
     Email: academicinterventionlab@utoronto.ca

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