Generic suggestion based systems often fail to personalize to user's context, and providing personalized specialist feedback is impossible to achieve at scale. Many of these applications either operate by prescribing generic suggestions or require direct intervention from a specialist to personalize. Mobile phone based behavior change applications have shown great promise for health management over the years. Incorporating an awareness of individual biochemical variations could have a significant impact on a wide range of technologies and help support increased well-being, productivity, and higher quality of sleep. Our findings demonstrate that phone usage patterns can be used to detect and predict individual daily variations indicative of temporal preference, sleep deprivation, and the effects of social jet lag.īeing able to unobtrusively measure biological misalignments means there is also an opportunity for technology to play to our biological strengths. This project focuses on identifying novel measurements and interventions that can leverage these daily variations. However, converging strands of research indicate that this is not the case - our biochemistry varies significantly over the course of a 24 hour period and consequently our levels of alertness, productivity, physical activity, and even sensitivity to pain can vary according to the time of day. We often think of ourselves as individuals with steady capabilities. Inspired by these previous studies we designed and built EmotionCheck, which is a watch-like device that can help users to regulate their anxiety by changing their perception of their own heart rate in a subtle way. In particular, previous studies show that the way we perceive our bodily signals can directly influence our emotional experience. In this project we argue that it is possible to do that by developing mobile interventions that focus on implicit emotion regulation, in which users are able to regulate their emotions without the need for conscious supervision or explicit intentions.
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Therefore, a crucial question that arises is: How to design mobile interventions that can help users to regulate their emotions in real-time, without compromising their behavior or cognition? However, many of the current interventions require a lot of attention and effort from the users, which may affect their concentration during ongoing tasks and even increase their stress. Researchers have devised different interventions to help users regulate their emotions. (4) Evaluation of Nutrilyzer for milk protein concentration, milk adulterants, and alcohol concentration characterization. (3) Implementation of the signal processing and machine learning algorithm for liquid food characterization. (2) Design and Implementation of a low-cost mobile photoacoustic sensing system.
This work made the following contributions: (1) Proving the fundamental concept of the theory of photoacoustic effect with step-by-step experimentation. The long-term vision of this work is to democratize food characterization using such a low cost, easy to use, mobile system which could enable consumers to test food before purchase and to put an indirect pressure on the food industry and government regulators to ensure quality. We took this fundamental physics concept to build a mobile sensing system that can characterize the quality or nutritional characteristics of liquid food. Photoacoustic effect is a fundamental physics concept which is essentially the generation of sound due to the absorption of intensity modulated light or more generally EM waves by a certain material. The results of these studies show the potential of automatic and less perceptible emotion regulation systems. In the other study, participants who listened to their own voices with a lower pitch during contentious debates felt more powerful.
In one study, participants that received voice feedback with a calmer tone during relationship conflicts felt less anxious.
We conducted two studies to evaluate the potential of this approach by automatically and subtly altering how people perceive their own voice. In this project, we propose a different approach inspired by self-perception theory: noticing that people are often reacting to the perception of their own behavior, we artificially change their perceptions to influence their emotions. This often limits their efficacy in practice.
Although several strategies and technological approaches have been proposed for emotion regulation, they often requireĬonscious attention and effort. Emotions play a major role in how interpersonal conflicts unfold.
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