Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Introduction to Motivation and Emotion01:29

Introduction to Motivation and Emotion

457
Motivation is a multifaceted process that drives behavior toward fulfilling various physiological or psychological needs. This process involves initiating, guiding, and maintaining specific actions influenced by internal and external factors. For example, when someone feels hungry while watching television, hunger is a motivator, prompting the individual to get up, walk to the kitchen, and find something to eat. In this instance, hunger initiates and sustains the behavior necessary to meet the...
457
Motivational Cycle01:20

Motivational Cycle

688
The motivational cycle is a key concept that explains how individuals are motivated to meet their needs. At its core, the cycle revolves around four distinct stages: need, drive, goal-directed behavior, and goal achievement. These stages respond to imbalances in the body or mind, prompting actions that restore balance.
The cycle begins with a need. This need can arise from various conditions, such as hunger, thirst, or temperature changes. For instance, when an individual feels cold, their body...
688
Drive-Reduction Theory: Push Theory of Motivation01:27

Drive-Reduction Theory: Push Theory of Motivation

500
Clark Hull's drive-reduction theory, introduced in the 1940s and 1950s and often termed the "push theory" of motivation, provides a framework for understanding how biological and learned drives influence behavior. Hull suggested that motivation originates from the need to alleviate physiological tension caused by unmet biological necessities. The theory proposes that when a basic need, such as hunger or sleep, goes unfulfilled, it creates an internal imbalance. This imbalance, or...
500
Ryan and Deci's Self-Determination Theory01:17

Ryan and Deci's Self-Determination Theory

12.8K
Self-Determination Theory (SDT), formulated by Richard Ryan and Edward Deci, explains that human motivation is driven by three fundamental psychological needs: autonomy, competence, and relatedness. When these needs are met, individuals experience personal growth, intrinsic motivation, and overall well-being.
Autonomy is the need to feel in control of one's actions and decisions. For example, a student who chooses their research topic is likely to be more engaged and motivated than one who...
12.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

MsWH: A Multi-Sensory Hardware Platform for Capturing and Analyzing Physiological Emotional Signals.

Sensors (Basel, Switzerland)·2022
Same author

Self-Calibration Technique with Lightweight Algorithm for Thermal Drift Compensation in MEMS Accelerometers.

Micromachines·2022
Same author

Lightweight Thermal Compensation Technique for MEMS Capacitive Accelerometer Oriented to Quasi-Static Measurements.

Sensors (Basel, Switzerland)·2021
See all related articles

Related Experiment Video

Updated: Aug 10, 2025

Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance
06:26

Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance

Published on: September 27, 2024

560

Wearables and Machine Learning for Improving Runners' Motivation from an Affective Perspective.

Sandra Baldassarri1, Jorge García de Quirós1, José Ramón Beltrán2

  • 1Computer Science and Systems Engineering Department, Engineering Research Institute of Aragon (I3A), University of Zaragoza, 50018 Zaragoza, Spain.

Sensors (Basel, Switzerland)
|February 11, 2023
PubMed
Summary

This study introduces a wearable device and machine learning models to detect runners' emotions using electrodermal activity. The DJ-Running project uses these real-time emotion insights to personalize music, enhancing training motivation and athlete well-being.

Keywords:
emotion recognitionmachine learningmusic recommendationrunningwearable devices

More Related Videos

A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings
10:45

A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings

Published on: January 22, 2018

7.7K
Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
12:51

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

Published on: June 16, 2018

7.6K

Related Experiment Videos

Last Updated: Aug 10, 2025

Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance
06:26

Author Spotlight: Exploring Breathing Techniques and Digital Solutions for Enhancing Running Performance

Published on: September 27, 2024

560
A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings
10:45

A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings

Published on: January 22, 2018

7.7K
Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
12:51

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

Published on: June 16, 2018

7.6K

Area of Science:

  • Sports Science
  • Affective Computing
  • Wearable Technology

Background:

  • Wearable technology is increasingly used in sports for performance enhancement and injury prevention.
  • Emotional states are crucial in athletic training but are often not monitored or utilized in real-time.
  • Existing solutions lack real-time emotion monitoring for personalized athlete support.

Purpose of the Study:

  • To develop a wearable system capable of real-time emotion recognition for runners.
  • To integrate emotion detection into a system that enhances athletic training quality and safety.
  • To leverage detected emotions for personalized motivation through music during training.

Main Methods:

  • Utilized electrodermal activity (EDA) as a physiological measure for emotion detection.
  • Developed machine learning models to analyze EDA data and infer runners' emotions.
  • Integrated the wearable device and models into the DJ-Running mobile application for real-time feedback.

Main Results:

  • Successfully developed a wearable system and machine learning models to deduce runners' emotions during training.
  • Demonstrated the feasibility of using electrodermal activity for emotion recognition in a running context.
  • Enabled real-time emotion-driven music selection to enhance runner motivation.

Conclusions:

  • Real-time emotion monitoring via wearables can significantly improve athletic training.
  • The DJ-Running system effectively uses physiological data to personalize the training experience.
  • This approach offers a novel method for enhancing athlete motivation and well-being through affective computing.