Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers
Physiological signals (e.g., heart rate, skin conductance) that were traditionally studied in neuroscientific laboratory research are currently being used in numerous real-life studies using wearable technology. Physiological signals obtained with wearables seem to offer great potential for continuo...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Behavioral Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnbeh.2022.856544/full |
| _version_ | 1818216100096114688 |
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| author | Peter de Looff Peter de Looff Peter de Looff Remko Duursma Matthijs Noordzij Sara Taylor Natasha Jaques Floortje Scheepers Kees de Schepper Saskia Koldijk |
| author_facet | Peter de Looff Peter de Looff Peter de Looff Remko Duursma Matthijs Noordzij Sara Taylor Natasha Jaques Floortje Scheepers Kees de Schepper Saskia Koldijk |
| author_sort | Peter de Looff |
| collection | DOAJ |
| description | Physiological signals (e.g., heart rate, skin conductance) that were traditionally studied in neuroscientific laboratory research are currently being used in numerous real-life studies using wearable technology. Physiological signals obtained with wearables seem to offer great potential for continuous monitoring and providing biofeedback in clinical practice and healthcare research. The physiological data obtained from these signals has utility for both clinicians and researchers. Clinicians are typically interested in the day-to-day and moment-to-moment physiological reactivity of patients to real-life stressors, events, and situations or interested in the physiological reactivity to stimuli in therapy. Researchers typically apply signal analysis methods to the data by pre-processing the physiological signals, detecting artifacts, and extracting features, which can be a challenge considering the amount of data that needs to be processed. This paper describes the creation of a “Wearables” R package and a Shiny “E4 dashboard” application for an often-studied wearable, the Empatica E4. The package and Shiny application can be used to visualize the relationship between physiological signals and real-life stressors or stimuli, but can also be used to pre-process physiological data, detect artifacts, and extract relevant features for further analysis. In addition, the application has a batch process option to analyze large amounts of physiological data into ready-to-use data files. The software accommodates users with a downloadable report that provides opportunities for a careful investigation of physiological reactions in daily life. The application is freely available, thought to be easy to use, and thought to be easily extendible to other wearable devices. Future research should focus on the usability of the application and the validation of the algorithms. |
| first_indexed | 2024-12-12T06:46:36Z |
| format | Article |
| id | doaj.art-47fd818f417a4257a9f8a49bc332c93d |
| institution | Directory Open Access Journal |
| issn | 1662-5153 |
| language | English |
| last_indexed | 2024-12-12T06:46:36Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Behavioral Neuroscience |
| spelling | doaj.art-47fd818f417a4257a9f8a49bc332c93d2022-12-22T00:34:11ZengFrontiers Media S.A.Frontiers in Behavioral Neuroscience1662-51532022-06-011610.3389/fnbeh.2022.856544856544Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and ResearchersPeter de Looff0Peter de Looff1Peter de Looff2Remko Duursma3Matthijs Noordzij4Sara Taylor5Natasha Jaques6Floortje Scheepers7Kees de Schepper8Saskia Koldijk9Behavioural Science Institute, Radboud University, Nijmegen, NetherlandsDe Borg, Den Dolder, NetherlandsFivoor Science and Treatment Innovation, Den Dolder, NetherlandsShintō Labs, Eindhoven, NetherlandsDepartment of Psychology, Health and Technology, University of Twente, Enschede, NetherlandsAffective Computing Group, Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United StatesAffective Computing Group, Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United StatesPsyData Group, Department of Psychiatry, UMC Utrecht, Utrecht, NetherlandsPsyData Group, Department of Psychiatry, UMC Utrecht, Utrecht, NetherlandsPsyData Group, Department of Psychiatry, UMC Utrecht, Utrecht, NetherlandsPhysiological signals (e.g., heart rate, skin conductance) that were traditionally studied in neuroscientific laboratory research are currently being used in numerous real-life studies using wearable technology. Physiological signals obtained with wearables seem to offer great potential for continuous monitoring and providing biofeedback in clinical practice and healthcare research. The physiological data obtained from these signals has utility for both clinicians and researchers. Clinicians are typically interested in the day-to-day and moment-to-moment physiological reactivity of patients to real-life stressors, events, and situations or interested in the physiological reactivity to stimuli in therapy. Researchers typically apply signal analysis methods to the data by pre-processing the physiological signals, detecting artifacts, and extracting features, which can be a challenge considering the amount of data that needs to be processed. This paper describes the creation of a “Wearables” R package and a Shiny “E4 dashboard” application for an often-studied wearable, the Empatica E4. The package and Shiny application can be used to visualize the relationship between physiological signals and real-life stressors or stimuli, but can also be used to pre-process physiological data, detect artifacts, and extract relevant features for further analysis. In addition, the application has a batch process option to analyze large amounts of physiological data into ready-to-use data files. The software accommodates users with a downloadable report that provides opportunities for a careful investigation of physiological reactions in daily life. The application is freely available, thought to be easy to use, and thought to be easily extendible to other wearable devices. Future research should focus on the usability of the application and the validation of the algorithms.https://www.frontiersin.org/articles/10.3389/fnbeh.2022.856544/fullwearablesheart rateelectrodermal activityR Shiny applicationneurosciencetreatment |
| spellingShingle | Peter de Looff Peter de Looff Peter de Looff Remko Duursma Matthijs Noordzij Sara Taylor Natasha Jaques Floortje Scheepers Kees de Schepper Saskia Koldijk Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers Frontiers in Behavioral Neuroscience wearables heart rate electrodermal activity R Shiny application neuroscience treatment |
| title | Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers |
| title_full | Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers |
| title_fullStr | Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers |
| title_full_unstemmed | Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers |
| title_short | Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers |
| title_sort | wearables an r package with accompanying shiny application for signal analysis of a wearable device targeted at clinicians and researchers |
| topic | wearables heart rate electrodermal activity R Shiny application neuroscience treatment |
| url | https://www.frontiersin.org/articles/10.3389/fnbeh.2022.856544/full |
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