LAtest about moodmetric in research
The Moodmetric smart ring for electrodermal activity measurement is an invention of a Finnish company Vigofere Oy. The inventor Henry Rimminen (Ph.D.) has a solid background in sensor technology and physiological measurements. He came up with the idea of incorporating the electrodermal activity (EDA) measurement into a ring in 2011. The measurement signal accuracy of the ring is comparable to laboratory devices and the research by the Finnish Institute of Occupational Health (Torniainen et al. 2015) has found the device valid for field research.
What is unique in the Moodmetric calculation
The Moodmetric index is calculated by an algorithm developed by Vigofere Oy. The aim is to provide reliable electrodermal activity measurement data for field research, when persons are measured in their normal surroundings 24/7.
The novelty in the Moodmetric technology is calculating a single number (i.e. the Moodmetric index / the MM level) that describes arousal of a person on a scale of 0 to 100. It is comparable among different users and is comparable among different skin dryness levels of one user. It is robust and resistant to motional artifacts.
Electrodermal activity measurement
Electrodermal activity (EDA) is one of the most studied psychophysiological markers of the functioning of the autonomic nervous system and it has been applied in psychophysiological research for over 100 years (Boucsein 2012). EDA is an indicator of the sympathetic activity of the autonomic nervous system that is associated with emotion, cognition, and affection (e.g. Critchley 2002). The phenomenon measured is also known as skin conductance (SC) and galvanic skin response (GSR).
Where to measure electrodermal activity
The skin becomes a better conductor of electricity when the eccrine sweat glands process sweat to skin surface. Eccrine glands are innervated by the sympathetic nervous system and are part of the fight or flight response system. The palmar site of the skin or sole provide the best measurement points due the great intensity of the eccrine sweat glands. (e.g. Boucsein 2012.)
Factors that may affect the measurement
Diseases relating to the functionality of the autonomic nervous system may affect electrodermal activity measurement. Patients with hyper- or hypothyroidism have been recorded with unusual EDA measurements (e.g. Dolu et al. 1997; Dolu et al. 1999). Within a variety of anxiety disorders (e.g. panic disorder and posttraumatic stress disorder), increased electrodermal activity and reactivity has been observed (Braune et al., 1994; Hoehn et al., 1997, Lader & Wing, 1964; Blechert et al., 2007). However, in depression electrodermal activity is often reduced (Argyle, 1991; Ward et al., 1983).
The measurement of the electrodermal activity raw signal is sensitive to motion. The signal needs processing to reduce noise. The Moodmetric algorithm is foremost developed to focus on this task.
Electrodermal activity measurement has not been largely applied in clinical research until now. It has been limited to laboratory environment before the entry of wearable devices.Download PDF with references here
There are little ambulatory measurement applications for stress available. Long term measurement is needed when a) wanting to understand is high stress load momentary or going on for weeks or months indicating chronic
stress b) motivating a person to efficient stress management with real time feedback. The Moodmetric smart ring fits these purposes well.
The Moodmetric measurement is well suited for preventive stress management in organizations and occupational health.
The Moodmetric ring and app
The Moodmetric smart ring measures electrodermal activity. It detects skin conductance with the band of the ring that works as electrodes. The band consists of two silver coated steel rings, and an insulator band in between them.
Moodmetric app is available for iOS and Android. The ring connects to the app via bluetooth and enables real-time monitoring.
Read more: http://www.moodmetric.com/stress-measurement-data/
The Moodmetric cloud service
From the mobile app it is possible to download the data to the Moodmetric cloud. The cloud enables long term remote monitoring, and uploading the data from the cloud to further analysis in csv or excel format.
The users can synchronize data from several smart rings to the cloud platform, and also export the data as CSV-file from the platform. The platform includes also a service for group monitoring, e.g. for monitoring the stress of teams or other organizational units. The platform provides also APIs for accessing the data and enabling to build third-party services.
The data sync from mobile to app is by default set to every three hours when within WiFi connection. The cloud data is thus possible to view almost real-time.
While the Moodmetric ring measurement sample rate is 3S/sec, the ring stores only 1 sample per minute. This is due to memory size limitation, and the intended use of the Moodmetric ring. The ring is primarily targeted to long term and continuous follow-up on stress levels, where the stored measurement points are sufficient. The stored ring data is transferred to cloud is thus also 1 sample per minute.
In the case of the Moodmetric smart ring, the data can be exported from the mobile device or accessed via the cloud. The most straightforward way is to download data from the cloud to excel or csv.
From the cloud the following data points can be accessed. However, for consumer use or long term stress management we always advice to use the indexed MM level. This is the most informative figure, and reliable also when the Moodmetric ring has been worn in normal circumstances. When the SCL or SCR levels are used, should a laboratory setting be applied.
From the cloud the datalog can be also downloaded as a CSV-file. The CSV-file is nearly identical with the datalog table presented above, however, the synchronization information is only stored in the mobile device and the CSV export from cloud contains device_id as additional variable.
API (Application Programming Interface)
The Moodmetric API makes it possible to benefit from data in the Moodmetric cloud. The Moodmetric API is a partner API type and available upon request. It is shared with companies building e.g. health data platforms. The aim is to increase use and awareness of the EDA signal by providing an open API to all requestors with appropriate solutions. Via the Moodmetric API it is possible to access the same datalog as described above.
SDK (Software developer KIT)
The Moodmetric SDK allows everyone to develop their own mobile applications using the Moodmetric measurement data. To ensure operation of 3rd party applications in any mobile platform or computer operating system, Moodmetric provides interface documentation directly to the ring. The platform running the 3rd party application must be bluetooth smart ready.
You can download the SDK for free here.
With the SDK you can access e.g. the Instant Indicator and the Moodmetric Index / the MM level.
The Instant indicator
The Instant indicator is a fast indicator on how the person reacts to different stimuli. These can be what you see, hear, smell or sense by touch at a certain moment. The response can be seen as an upward spike, which starts approximately after 1.5 seconds after the stimulus and peaks approximately after 2.5-3.0 seconds
The Moodmetric Index
The Moodmetric Index / the MM level is a continuous indicator on the wearer´s stress level on a scale of 0 too 100. The index is resistant to motional artefacts and comparable among different users.
Access raw data with the Windows PC logging software
The Moodmetric ring does not store raw data due to limited memory size. The Moodmetric ring measurement raw data can be accessed only by direct streaming from the ring to a Windows PC via a certain type of BLE dongle.
You can download a free package with drivers and short instructions here. Please note that this tool is primarily for research use, and we can not provide excessive user support for it.
Päivi Heikkilä, Anita Honka, Sebastian Mach, Franziska Schmalfuß, Eija Kaasinen and Kaisa Väänänen. 2018. Quantified Factory Worker: Expert Evaluation and Ethical Considerations of Wearable Self-tracking Devices. In Proceedings of Academic Mindtrek conference (Mindtrek 2018). ACM, Tampere, Finland, 10 pages.
Jussila, J., Venho, N., Salonius, H., Moilanen, J., Liukkonen, J., & Rinnetmäki, M. (2018, October). Towards ecosystem for research and development of electrodermal activity applications. In Proceedings of the 22nd International Academic Mindtrek Conference (pp. 79-87). ACM.
Jari Torniainen, Benjamin Cowley, Andreas Henelius, Kristian Lukander, Satu Pakarinen. 2015. Feasibility of an electrodermal activity ring prototype as a research tool. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
Jari Torniainen, Benjamin Cowley. 2016. A short review and primer on electrodermal activity in human computer interaction applications (Benjamin Ultan Cowley, Jari Torniainen)
University cooperation and research projects: Niina Venho – [email protected] +358 40 710 4087