Using smartphones to collect behavioral data in psychological science: Opportunities, practical considerations, and challenges
Smartphones now offer the promise of collecting behavioral data unobtrusively, in situ, as it
unfolds in the course of daily life. Data can be collected from the onboard sensors and other …
unfolds in the course of daily life. Data can be collected from the onboard sensors and other …
Personal sensing: understanding mental health using ubiquitous sensors and machine learning
Sensors in everyday devices, such as our phones, wearables, and computers, leave a
stream of digital traces. Personal sensing refers to collecting and analyzing data from …
stream of digital traces. Personal sensing refers to collecting and analyzing data from …
Psychological targeting as an effective approach to digital mass persuasion
People are exposed to persuasive communication across many different contexts:
Governments, companies, and political parties use persuasive appeals to encourage people …
Governments, companies, and political parties use persuasive appeals to encourage people …
A review, current challenges, and future possibilities on emotion recognition using machine learning and physiological signals
The seminal work on Affective Computing in 1995 by Picard set the base for computing that
relates to, arises from, or influences emotions. Affective computing is a multidisciplinary field …
relates to, arises from, or influences emotions. Affective computing is a multidisciplinary field …
Emotion recognition using wireless signals
This paper demonstrates a new technology that can infer a person's emotions from RF
signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections …
signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections …
[HTML][HTML] Mental health monitoring with multimodal sensing and machine learning: A survey
Personal and ubiquitous sensing technologies such as smartphones have allowed the
continuous collection of data in an unobtrusive manner. Machine learning methods have …
continuous collection of data in an unobtrusive manner. Machine learning methods have …
Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis
One of the most interesting applications of mobile sensing is monitoring of individual
behavior, especially in the area of mental health care. Most existing systems require an …
behavior, especially in the area of mental health care. Most existing systems require an …
Personalized multitask learning for predicting tomorrow's mood, stress, and health
While accurately predicting mood and wellbeing could have a number of important clinical
benefits, traditional machine learning (ML) methods frequently yield low performance in this …
benefits, traditional machine learning (ML) methods frequently yield low performance in this …
Smartphone sensing methods for studying behavior in everyday life
Highlights•Smartphone Sensing Methods (SSMs) permit continuous and real-time
behavioral observation in the context of people's daily lives.•SSMs provide objective …
behavioral observation in the context of people's daily lives.•SSMs provide objective …
Smartphone-based recognition of states and state changes in bipolar disorder patients
Today's health care is difficult to imagine without the possibility to objectively measure
various physiological parameters related to patients' symptoms (from temperature through …
various physiological parameters related to patients' symptoms (from temperature through …