3 research outputs found
Affective Umbrella β A Wearable System to Visualize Heart and Electrodermal Activity, towards Emotion Regulation through Somaesthetic Appreciation
In this paper, we introduce Affective Umbrella, a novel system to record, analyze and visualize physiological data in real time via an umbrella handle. We implement a biofeedback loop design in the system that triggers visualization changes to reflect and regulate emotions through somaesthetic appreciation. We report the methodology, processes, and results of data reliability and visual feedback impact on emotions. We evaluated the system using a real-life user study (n=21) in rainy weather at night. The statistical results demonstrate the potential of applying the visualization of biofeedback to regulate emotional arousal with a significantly higher (p=.0022) score, a lower (p=.0277) dominance than baseline from self-reported SAM Scale, and physiological arousal, which was shown to be significantly increased (p<.0001) with biofeedback in terms of pNN50 and a significant difference in terms of RMSSD. There was no significant difference in terms of emotional valence changes from SAM scale. Furthermore, we compared the difference between two biofeedback patterns (mirror and inversion). The mirror effect was with a significantly higher emotional arousal than the inversion effect (p=.0277) from SAM results and was with a significantly lower RMSSD performance than the inversion effect (p<.0001). This work demonstrates the potential for capturing physiological data using an umbrella handle and using this data to influence a userβs emotional state via lighting effects
ΠΠ΅ΡΠΎΠ΄Π΅ Π·Π° ΠΎΡΠ΅Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π³Π»Π°ΡΠΊΠΈΡ ΠΌΠΈΡΠΈΡΠ°
Recording of the smooth stomach muscles' electrical activity can be performed by means of Electrogastrography (EGG), a non-invasive technique for acquisition that can provide valuable information regarding the functionality of the gut. While this method had been introduced for over nine decades, it still did not reach its full potential. The main reason for this is the lack of standardization that subsequently led to the limited reproducibility and comparability between different investigations. Additionally, variability between many proposed recording approaches could make EGG unappealing for broader application.
The aim was to provide an evaluation of a simplified recording protocol that could be obtained by using only one bipolar channel for a relatively short duration (20 minutes) in a static environment with limited subject movements. Insights into the most suitable surface electrode placement for EGG recording was also presented. Subsequently, different processing methods, including Fractional Order Calculus and Video-based approach for the cancelation of motion artifacts β one of the main pitfalls in the EGG technique, was examined.
For EGG, it is common to apply long-term protocols in a static environment. Our second goal was to introduce and investigate the opposite approach β short-term recording in a dynamic environment. Research in the field of EGG-based assessment of gut activity in relation to motion sickness symptoms induced by Virtual Reality and Driving Simulation was performed. Furthermore, three novel features for the description of EGG signal (Root Mean Square, Median Frequency, and Crest Factor) were proposed and its applicability for the assessment of gastric response during virtual and simulated experiences was evaluated.
In conclusion, in a static environment, the EGG protocol can be simplified, and its duration can be reduced. In contrast, in a dynamic environment, it is possible to acquire a reliable EGG signal with appropriate recommendations stated in this Doctoral dissertation. With the application of novel processing techniques and features, EGG could be a useful tool for the assessment of cybersickness and simulator sickness.Π‘Π½ΠΈΠΌΠ°ΡΠ΅ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π³Π»Π°ΡΠΊΠΈΡ
ΠΌΠΈΡΠΈΡΠ° ΠΆΠ΅Π»ΡΡΠ° ΠΌΠΎΠΆΠ΅ ΡΠ΅ ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°ΡΠΈ ΡΠΏΠΎΡΡΠ΅Π±ΠΎΠΌ Π΅Π»Π΅ΠΊΡΡΠΎΠ³Π°ΡΡΡΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ (ΠΠΠ), Π½Π΅ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ ΠΊΠΎΡΠ° ΠΏΡΡΠΆΠ° Π·Π½Π°ΡΠ°ΡΠ½Π΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡΠ΅ Π²Π΅Π·Π°Π½Π΅ Π·Π° ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠ°ΡΠ΅ ΠΎΡΠ³Π°Π½Π° Π·Π° Π²Π°ΡΠ΅ΡΠ΅. Π£ΠΏΡΠΊΠΎΡΡ ΡΠΈΡΠ΅Π½ΠΈΡΠΈ Π΄Π° ΡΠ΅ ΠΎΡΠΊΡΠΈΠ²Π΅Π½Π° ΠΏΡΠ΅ Π²ΠΈΡΠ΅ ΠΎΠ΄ Π΄Π΅Π²Π΅Ρ Π΄Π΅ΡΠ΅Π½ΠΈΡΠ°, ΠΎΠ²Π° ΡΠ΅Ρ
Π½ΠΈΠΊΠ° ΡΠΎΡ ΡΠ²Π΅ΠΊ Π½ΠΈΡΠ΅ ΠΎΡΡΠ²Π°ΡΠΈΠ»Π° ΡΠ²ΠΎΡ ΠΏΡΠ½ ΠΏΠΎΡΠ΅Π½ΡΠΈΡΠ°Π». ΠΡΠ½ΠΎΠ²Π½ΠΈ ΡΠ°Π·Π»ΠΎΠ³ Π·Π° ΡΠΎ ΡΠ΅ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠ°ΠΊ ΡΡΠ°Π½Π΄Π°ΡΠ΄ΠΈΠ·Π°ΡΠΈΡΠ΅ ΠΊΠΎΡΠΈ ΡΡΠ»ΠΎΠ²ΡΠ°Π²Π° ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅ΡΠ° Ρ ΡΠΌΠΈΡΠ»Ρ ΠΏΠΎΠ½ΠΎΠ²ΡΠΈΠ²ΠΎΡΡΠΈ ΠΈ ΡΠΏΠΎΡΠ΅Π΄ΠΈΠ²ΠΎΡΡΠΈ ΠΈΠ·ΠΌΠ΅ΡΡ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ°. ΠΠΎΠ΄Π°ΡΠ½ΠΎ, Π²Π°ΡΠΈΡΠ°Π±ΠΈΠ»Π½ΠΎΡΡ ΠΊΠΎΡΠ° ΡΠ΅ ΠΏΡΠΈΡΡΡΠ½Π° Ρ ΠΏΡΠΈΠΌΠ΅Π½ΠΈ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
ΠΏΡΠ΅ΠΏΠΎΡΡΡΠ΅Π½ΠΈΡ
ΠΏΠΎΡΡΡΠΏΠ°ΠΊΠ° ΡΠ½ΠΈΠΌΠ°ΡΠ°, ΠΌΠΎΠΆΠ΅ ΡΠΌΠ°ΡΠΈΡΠΈ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ Π·Π° ΡΠΏΠΎΡΡΠ΅Π±Ρ ΠΠΠ-Π° ΠΊΠΎΠ΄ ΡΠΈΡΠΎΠΊΠΎΠ³ ΠΎΠΏΡΠ΅Π³Π° ΠΏΠΎΡΠ΅Π½ΡΠΈΡΠ°Π»Π½ΠΈΡ
ΠΊΠΎΡΠΈΡΠ½ΠΈΠΊΠ°.
ΠΠ°Ρ ΡΠΈΡ ΡΠ΅ Π±ΠΈΠΎ Π΄Π° ΠΏΡΡΠΆΠΈΠΌΠΎ Π΅Π²Π°Π»ΡΠ°ΡΠΈΡΡ ΠΏΠΎΡΠ΅Π΄Π½ΠΎΡΡΠ°Π²ΡΠ΅Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ ΠΌΠ΅ΡΠ΅ΡΠ° ΡΡ. ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π° ΠΊΠΎΡΠΈ ΡΠΊΡΡΡΡΡΠ΅ ΡΠ°ΠΌΠΎ ΡΠ΅Π΄Π°Π½ ΠΊΠ°Π½Π°Π» ΡΠΎΠΊΠΎΠΌ ΡΠ΅Π»Π°ΡΠΈΠ²Π½ΠΎ ΠΊΡΠ°ΡΠΊΠΎΠ³ Π²ΡΠ΅ΠΌΠ΅Π½ΡΠΊΠΎΠ³ ΠΏΠ΅ΡΠΈΠΎΠ΄Π° (20 ΠΌΠΈΠ½ΡΡΠ°) Ρ ΡΡΠ°ΡΠΈΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ° ΡΠ° ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΈΠΌ ΠΊΡΠ΅ΡΠ°ΡΠ΅ΠΌ ΡΡΠ±ΡΠ΅ΠΊΡΠ° ΡΡ. Ρ ΠΌΠΈΡΠΎΠ²Π°ΡΡ. Π’Π°ΠΊΠΎΡΠ΅, ΠΏΡΠΈΠΊΠ°Π·Π°Π»ΠΈ ΡΠΌΠΎ Π½Π°ΡΠ΅ ΡΡΠ°Π²ΠΎΠ²Π΅ Ρ Π²Π΅Π·ΠΈ Π½Π°ΡΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΈΡΠ΅ ΠΏΠΎΠ·ΠΈΡΠΈΡΠ΅ ΠΏΠΎΠ²ΡΡΠΈΠ½ΡΠΊΠΈΡ
Π΅Π»Π΅ΠΊΡΡΠΎΠ΄Π° Π·Π° ΠΠΠ ΡΠ½ΠΈΠΌΠ°ΡΠ΅. ΠΡΠ΅Π·Π΅Π½ΡΠΎΠ²Π°Π»ΠΈ ΡΠΌΠΎ ΠΈ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠ΅ ΠΈΡΠΏΠΈΡΠΈΠ²Π°ΡΠ° ΠΌΠ΅ΡΠΎΠ΄Π°, Π½Π° Π±Π°Π·ΠΈ ΠΎΠ±ΡΠ°Π΄Π΅ Π²ΠΈΠ΄Π΅ΠΎ ΡΠ½ΠΈΠΌΠΊΠ° ΠΊΠ°ΠΎ ΠΈ ΡΡΠ°ΠΊΡΠΈΠΎΠ½ΠΎΠ³ Π΄ΠΈΡΠ΅ΡΠ΅Π½ΡΠΈΡΠ°Π»Π½ΠΎΠ³ ΡΠ°ΡΡΠ½Π°, Π·Π° ΠΎΡΠΊΠ»Π°ΡΠ°ΡΠ΅ Π°ΡΡΠ΅ΡΠ°ΠΊΠ°ΡΠ° ΠΏΠΎΠΌΠ΅ΡΠ°ΡΠ° β ΡΠ΅Π΄Π½ΠΎΠ³ ΠΎΠ΄ Π½Π°ΡΠ²Π΅ΡΠΈΡ
ΠΈΠ·Π°Π·ΠΎΠ²Π° ΡΠ° ΠΊΠΎΡΠΈΠΌΠ° ΡΠ΅ ΡΡΠΎΡΠ΅Π½Π° ΠΠΠ ΠΌΠ΅ΡΠΎΠ΄Π°.
ΠΠ° ΠΠΠ ΡΠ΅ ΡΠΎΠ±ΠΈΡΠ°ΡΠ΅Π½ΠΎ Π΄Π° ΡΠ΅ ΠΊΠΎΡΠΈΡΡΠ΅ Π΄ΡΠ³ΠΎΡΡΠ°ΡΠ½ΠΈ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»ΠΈ Ρ ΡΡΠ°ΡΠΈΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ°. ΠΠ°Ρ Π΄ΡΡΠ³ΠΈ ΡΠΈΡ Π±ΠΈΠΎ ΡΠ΅ Π΄Π° ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΠΈΠΌΠΎ ΠΈ ΠΎΡΠ΅Π½ΠΈΠΌΠΎ ΡΠΏΠΎΡΡΠ΅Π±ΡΠΈΠ²ΠΎΡΡ ΡΡΠΏΡΠΎΡΠ½ΠΎΠ³ ΠΏΡΠΈΡΡΡΠΏΠ° β ΠΊΡΠ°ΡΠΊΠΎΡΡΠ°ΡΠ½ΠΈΡ
ΡΠ½ΠΈΠΌΠ°ΡΠ° Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ°. Π Π΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π»ΠΈ ΡΠΌΠΎ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ΅ Π½Π° ΠΏΠΎΡΡ ΠΎΡΠ΅Π½Π΅ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΆΠ΅Π»ΡΡΠ° ΡΠΎΠΊΠΎΠΌ ΠΏΠΎΡΠ°Π²Π΅ ΡΠΈΠΌΠΏΡΠΎΠΌΠ° ΠΌΡΡΠ½ΠΈΠ½Π΅ ΠΈΠ·Π°Π·Π²Π°Π½Π΅ Π²ΠΈΡΡΡΠ΅Π»Π½ΠΎΠΌ ΡΠ΅Π°Π»Π½ΠΎΡΡΡ ΠΈ ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠΎΠΌ Π²ΠΎΠΆΡΠ΅. ΠΠ° ΠΏΠΎΡΡΠ΅Π±Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ Π·Π° ΠΎΡΠ΅Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΆΠ΅Π»ΡΡΠ°, ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠΈΠ»ΠΈ ΡΠΌΠΎ ΡΡΠΈ Π½ΠΎΠ²Π° ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ° Π·Π° ΠΊΠ²Π°Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡΡ ΠΠΠ ΡΠΈΠ³Π½Π°Π»Π° (Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½Ρ Π²ΡΠ΅Π΄Π½ΠΎΡΡ Π°ΠΌΠΏΠ»ΠΈΡΡΠ΄Π΅, ΠΌΠ΅Π΄ΠΈΡΠ°Π½Ρ ΠΈ ΠΊΡΠ΅ΡΡ ΡΠ°ΠΊΡΠΎΡ) ΠΈ ΠΈΠ·Π²ΡΡΠΈΠ»ΠΈ ΠΏΡΠΎΡΠ΅Π½Ρ ΡΠΈΡ
ΠΎΠ²Π΅ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΡΡΠΈ Π·Π° ΠΎΡΠ΅Π½Ρ Π³Π°ΡΡΡΠΎΠΈΠ½ΡΠ΅ΡΡΠΈΠ½Π°Π»Π½ΠΎΠ³ ΡΡΠ°ΠΊΡΠ° ΡΠΎΠΊΠΎΠΌ ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ° Π²ΠΈΡΡΡΠ΅Π»Π½Π΅ ΡΠ΅Π°Π»Π½ΠΎΡΡΠΈ ΠΈ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° Π²ΠΎΠΆΡΠ΅.
ΠΠ°ΠΊΡΡΡΠ°ΠΊ ΡΠ΅ Π΄Π° ΠΠΠ ΠΏΡΠΎΡΠΎΠΊΠΎΠ» Ρ ΡΡΠ°ΡΠΈΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ° ΠΌΠΎΠΆΠ΅ Π±ΠΈΡΠΈ ΡΠΏΡΠΎΡΡΠ΅Π½ ΠΈ ΡΠ΅Π³ΠΎΠ²ΠΎ ΡΡΠ°ΡΠ°ΡΠ΅ ΠΌΠΎΠΆΠ΅ Π±ΠΈΡΠΈ ΡΠ΅Π΄ΡΠΊΠΎΠ²Π°Π½ΠΎ, Π΄ΠΎΠΊ ΡΠ΅ Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΌΠ° ΠΌΠΎΠ³ΡΡΠ΅ ΡΠ½ΠΈΠΌΠΈΡΠΈ ΠΎΠ΄Π³ΠΎΠ²Π°ΡΠ°ΡΡΡΠΈ ΠΠΠ ΡΠΈΠ³Π½Π°Π», Π°Π»ΠΈ ΡΠ· ΠΏΡΠ°ΡΠ΅ΡΠ΅ ΠΏΡΠ΅ΠΏΠΎΡΡΠΊΠ° Π½Π°Π²Π΅Π΄Π΅Π½ΠΈΡ
Ρ ΠΎΠ²ΠΎΡ ΡΠ΅Π·ΠΈ. Π£ΠΏΠΎΡΡΠ΅Π±ΠΎΠΌ Π½ΠΎΠ²ΠΈΡ
ΡΠ΅Ρ
Π½ΠΈΠΊΠ° Π·Π° ΠΏΡΠΎΡΠ΅ΡΠΈΡΠ°ΡΠ΅ ΡΠΈΠ³Π½Π°Π»Π° ΠΈ ΠΏΡΠΎΡΠ°ΡΡΠ½ ΠΎΠ΄Π³ΠΎΠ²Π°ΡΠ°ΡΡΡΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΠ°ΡΠ°, ΠΠΠ ΠΌΠΎΠΆΠ΅ Π±ΠΈΡΠΈ ΠΊΠΎΡΠΈΡΠ½Π° ΡΠ΅Ρ
Π½ΠΈΠΊΠ° Π·Π° ΠΎΡΠ΅Π½Ρ ΠΌΡΡΠ½ΠΈΠ½Π΅ ΠΈΠ·Π°Π·Π²Π°Π½Π΅ ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ΠΌ ΡΠΈΠΌΡΠ»Π°ΡΠΎΡΠ° ΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π° Π²ΠΈΡΡΡΠ΅Π»Π½Π΅ ΡΠ΅Π°Π»Π½ΠΎΡΡ
Considering Gut Biofeedback for Emotion Regulation
International audienceRecent research in the enteric nervous system, sometimes called the second brain, has revealed potential of the digestive system in predicting emotion. Even though people regularly experience changes in their gastrointestinal (GI) tract which influence their mood and behavior multiple times per day, robust measurements and wearable devices are not quite developed for such phenomena. However, other manifestations of the autonomic nervous system such as electrodermal activity, heart rate, and facial muscle movement have been extensively used as measures of emotions or in biofeedback applications, while neglecting the gut. We expose electrogastrography (EGG), i.e., recordings of the myoelectric activity of the GI tract, as a possible measure for inferring human emotions. In this paper, we also wish to bring into light some fundamental questions about emotions, which are often taken for granted in the field of Human Computer Interaction, but are still a great debate in the fields of cognitive neuroscience and psychology