Is Wearable Technology Becoming Part of Us? Developing and Validating a Measurement Scale for Wearable Technology Embodiment

Nelson, Elizabeth C.; Verhagen, Tibert; Vollenbroek-Hutten, Miriam Marie Rosé; Noordzij, Matthijs Leendert

doi:10.2196/12771

Cited by 20 publications

(15 citation statements)

References 80 publications

(104 reference statements)

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“…Individuals are increasingly wearing devices on their bodies, which monitor their behavior and provide coaching through associated apps. On one hand, the interaction with these types of devices might result in a sustained experience, where technology extends the body [1-3], cognition, and even self, which was recently conceptualized as wearable technology embodiment [4]. This is in line with other work in which wearables were referred to as cognitive prostheses [5,6].…”

Section: Introductionmentioning

confidence: 78%

“…Finally, this study compared a typical "dumb" physical prosthesis to a "smart" wearable, which are two areas already merging into a shared space. This research provides important insights into the experience of future "smart" prostheses and technologies already embodied by our bodies and minds [4].…”

Section: Limitations and Future Researchmentioning

confidence: 98%

“…Our comparison of wearables to initial smartphone experiences suggests that wearables could have similar reactions to the technology, especially as the technology innovates. Research has found that individuals can create an emotional attachment to their mobile phones [53], and literature within mobile technology interaction has proven that individuals can believe their phones are extensions of themselves [4,8,54,55].…”

Section: Principal Findingsmentioning

confidence: 99%

“…All three themes examine the integral connection of the brain to the prosthesis. Research has suggested that technology may interlace with our minds to take over some tasks, such as navigation [34], and take on new ones, such as quantifying sleep and activity [4,26]. Clark [35] argued that cell phones were not simply technological tools but upgrades of the mind.…”

Section: Introductionmentioning

confidence: 99%

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Embodiment of Wearable Technology: Qualitative Longitudinal Study

Nelson

Sools

Vollenbroek-Hutten³

et al. 2020

JMIR Mhealth Uhealth

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Background Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology. Objective In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern. Methods We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray’s work was combined with an inductive approach in which new themes were discovered. Results Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of “whom” to believe, the machine or one’s self. Conclusions There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally “dumb” body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.

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Section: Introductionmentioning

confidence: 78%

Section: Limitations and Future Researchmentioning

confidence: 98%

Section: Principal Findingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Embodiment of Wearable Technology: Qualitative Longitudinal Study

Nelson

Sools

Vollenbroek-Hutten³

et al. 2020

JMIR Mhealth Uhealth

Self Cite

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“…In either case, user-feedback data is invaluable for assessing participants' experiences of comfort/discomfort, device obtrusiveness, and the intuitiveness of user-interfaces (e.g., ease of starting/stopping recording, putting on and taking off devices either alone or with help) (Nelson et al, 2019;Spagnolli et al, 2014).…”

Section: Framework For Selecting and Benchmarking Mobile Devices In Pmentioning

confidence: 99%

Framework for Selecting and Benchmarking Mobile Devices in Psychophysiological Research

Kleckner¹,

Feldman²,

Goodwin³

et al. 2019

Preprint

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Commercially available consumer electronics (smartwatches and wearable biosensors) are increasingly enabling acquisition of peripheral physiological and physical activity data inside and outside of laboratory settings. However, there is scant literature available for selecting and assessing the suitability of these novel devices for scientific use. To overcome this limitation, the current paper offers a framework to aid researchers in choosing and evaluating wearable technologies for use in empirical research. Our seven-step framework includes: (1) identifying signals of interest; (2) characterizing intended use cases; (3) identifying study-specific pragmatic needs; (4) selecting devices for evaluation; (5) establishing an assessment procedure; (6) performing qualitative and quantitative analyses on resulting data; and, if desired, (7) conducting power analyses to determine sample size needed to more rigorously compare performance across devices. We illustrate the application of the framework by comparing electrodermal, cardiovascular, and accelerometry data from a variety of commercial wireless sensors (Affectiva Q, Empatica E3, Empatica E4, Actiwave Cardio, Shimmer) relative to a well-validated, wired Mindware laboratory system. Our evaluations are performed in two studies (N=10, N=11) involving psychometrically sound, standardized tasks that include physical activity and affect induction. After applying our framework to this data, we conclude that only some commercially available consumer devices for physiological measurement are capable of wirelessly measuring peripheral physiological and physical activity data of sufficient quality for scientific use cases. Thus, the framework appears to be beneficial at suggesting steps for conducting more systematic, transparent, and rigorous evaluations of mobile physiological devices prior to deployment in studies.

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The Relationship Between Diagnosed Burnout and Sleep Measured by Activity Trackers: Four Longitudinal Case Studies

Nelson

Keijzer

Vollenbroek-Hutten

et al. 2019

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Employee burnout is an increasing global problem. Some countries, such as The Netherlands, diagnose and treat burnout as a medical condition. While deficient sleep has been implicated as the primary risk factor for burnout, the longest current sleep measurement of burnout individuals is 4 weeks; and no studies have measured sleep throughout the burnout process (i.e.: pre-burnout, burnout diagnosis, recovery time, and returning to work). During a 7 month longitudinal study on wearable technology use, 4 participants were diagnosed with (pre)burnout by their company doctor using the Maslach's Burnout Inventory (MBI). Our study captured the participants' sleep data including: sleep quality, number of awakenings, sleep duration, time awake, and amount of light sleep during the burnout and recovery process. One participant experienced a burnout diagnosis, recovery at home, and returning to work within the 7 months providing the first look at sleep trends during the entire burnout process. Our results show that the burnout participants experienced decreased sleep quality (n = 2), sleep duration (n = 2), and light sleep (n = 3). In contrast, a sample of 3 non-burnout participants sleep remained stable on all measures except for time awake for one participant. The results of this study answer past calls for longer analysis of sleep's influence on burnout and highlight the vast opportunity to extend burnout research using the millions of active devices currently in use.

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Is Wearable Technology Becoming Part of Us? Developing and Validating a Measurement Scale for Wearable Technology Embodiment

Cited by 20 publications

References 80 publications

Embodiment of Wearable Technology: Qualitative Longitudinal Study

Embodiment of Wearable Technology: Qualitative Longitudinal Study

Framework for Selecting and Benchmarking Mobile Devices in Psychophysiological Research

The Relationship Between Diagnosed Burnout and Sleep Measured by Activity Trackers: Four Longitudinal Case Studies

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