Moodmetric app now with Diary and more

The Moodmetric ring and app support stress management with the aid of health tech. The app is a simple and visual tool that helps the user to understand and react to stressful things in life.

The new Moodmetric App has now been released for both iPhone and Android users. The app works with current and new ring versions.

The new app gives more tools for stress management

The familiar features of the previous Moodmetric app are still there. The real-time view supports live follow-up on stress levels, and the much appreciated Daily diagram is as before.

The new app supports stress management even better with both more possibilities for user input and automatized analytics. Defining actions and categorizing events show clearly what are the stressors in life, and what brings energy.

Stress/Mood scatter plot

The most impactful new feature is the Stress/Mood scatter plot, that now combines the experienced mood in addition to the stress measurement data provided by the Moodmetric ring.

The Moodmetric level 0-100 is the vertical axis of the scatter plow. The same Moodmetric level is familiar from the previous app version, it is developed for simple reading of the measurement results. The higher the stress level, the higher the vertical position of the life category circles.

The self perceived mood is the horizontal axis. The more use the has noted an event to be of a positive mood, to more to the right it takes the life category circle.

Diary

The scatter plot is based on Diary which is automatically updated with the Moodmetric stress level information. The user can download the phone calendar events to Diary and add notes.

It is possible to add notes to events, choose a category and indicate happy, neutral or bad mood.

 

App development is team work

Planning and development of the new features have  been started at Moodmetric already in spring 2017. We would like to give special thanks to Eero Jaakonaho for the work on perfecting the user experience from the visual perspective.

Both the iOS and Android mobile app new features have been developed at Gofore, in close cooperation with Moodmetric. The end user was kept in mind throughout the project, for example the developers had the possibility to wear the Moodmetric ring. Flexible communication enabled a smooth progress, and the app release was made as planned well before the new ring version deliveries.

Download the new Moodmetric app from AppStore or GooglePlay. If you have an old version with data in, you will not loose it.

Moodmetric features: Scope and Wearing the ring

MoodScope curve

Scope tells about the instantaneous reactions of the wearer. When you feel something, your autonomous nervous system reacts and small changes can be measured from your skin.

The Moodmetric Ring detects the changes that can be followed online with the smartphone app. All the reactions cause an upward jump on the Scope, the bigger the emotion, the higher the curve goes. The physical response delay is 1.5 seconds, so the jump is visible 1.5 s after seeing a ghost… Continue reading “Moodmetric features: Scope and Wearing the ring”

What is moodtech? – Science behind Moodmetric

Moodmetric measures the electrodermal activity (EDA) of the skin, which is widely adopted in psychological research 1. EDA is generated by activity of the sweat glands.  Moodmetric measures the palmar skin on your finger. The palmar skin is the recommended EDA measurement location, since it has the highest sweat gland density2.

The unconscious actions of the human body are regulated by the autonomic nervous system. It consists of the sympathetic part and the parasympathetic part. The parasympathetic part controls the body’s rest-and-digest functions and the sympathetic part controls fight-or-flight reactions. When bodily functions are not of interest and the emotional side is, sympathetic nervous system is your choice.

The sweat glands are exclusively innervated by the sympathetic nervous system. This makes EDA an ideal measure for sympathetic activation.2 Electrodermal activity correlates to general emotional intensity, negative emotion, concern, and anxiety. 1, 3 These emotions cause almost similar electrodermal responses, which makes them very hard to differentiate. However, Moodmetric will tell you if certain parts of your day have brought up emotions or not. Inversely, Moodmetric tells you weather you are calm or not. This is particularly useful during your mindfulness, meditation and other calming exercises.

Mobile EDA devices have been used by scientists for some time2, 4, and now we bring this technology within everyone´s reach.

Signal accuracy

The signal accuracy has been proven in a study of 24 people by the Finnish Institute of Occupational Health by J. Torniainen et al.. The accuracy against a laboratory grade reference was found to be 83 %. They conclude:

“Clearly the ring sensor can be used to measure a valid EDA signal as indicated by the similarity of both event-related responses and the calculated features. The accuracy of the Moodmetric EDA Ring is adequate for psychological and physiological research when weighted against the advantage of conducting ecologically valid experiments outside laboratory conditions.”

The results have been accepted for publication in the 2015 conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015, August 25-29).

Our measurement has been proven to be accurate also by University of Tampere, Finland. The correlation with the reference equipment Nexus-10-MK II was good. Comparison details in charts below.

image1 image2 image3 image4

1 Mendes, W.B. (2009). Assessing the autonomic nervous system. In: Harmon-Jones   E. ja Beer J.S. Methods in social neuroscience. New York: Guilford Press. p. 118-147.

2 Setz C., Arnrich B., Schumm J. and La R. (2010) Discriminating Stress From Cognitive Load Using a Wearable EDA Device. IEEE Trans. Inf. Technol. Biomed. 14(2). p. 410-417.

3 Nikula R. (1991) Psychological correlates of nonspecific skin conductance responses. Psychophysiology. 28(1). p.86-90.

4 Poh M.Z, Swenson N.C. and Picard R.W. (2010) A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity. IEEE Trans. Biomed. Eng. 57(4). p. 1243-1252.

 

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