Stress recognition
A wide variety of conditions, situations and pressure can cause stress to any one person at any given moment. Recognizing stress from wearable sensors or facial expressions is not convenient as the former needs to be worn continuously which may or may not be pervasive in nature and the later poses p
2025-06-28 16:36:09 - Adil Khan
Stress recognition
Project Area of Specialization Artificial IntelligenceProject SummaryA wide variety of conditions, situations and pressure can cause stress to any one person at any given moment. Recognizing stress from wearable sensors or facial expressions is not convenient as the former needs to be worn continuously which may or may not be pervasive in nature and the later poses privacy constraints. Moreover, the facial expressions for stress recognition can be enacted which may or may not result in false alarms. We propose stress detection using smart phones which are pervasive in nature and more importantly users carry them without concerning them as a hurdle. Furthermore, the ubiquitous nature of smart phones allows collecting data easily and has ability to recognize the stress, effectively.
Project Objectives- To collect the data from students with induced stress based on the conditions.
- To collect the data from students using their self-reporting.
- To comprehend the stress recognition using various machine learning approaches.
- To derive statistical as well as inferential insights based on the recognition outcomes.
In this work, we intend to collect the data from many students as the students are more susceptible to the stress, using their self-reporting and the conditions we choose to collect their data such as during midterms, exams, presentations, and so forth. We then, will be able to comprehend the stress using machine learning approaches.
ACCELEROMETER:
Accelerometer refers to the inertial sensor which computes the linear acceleration of the wearer in X, Y, and Z direction.
GYROSCOPE:
Gyroscope is also an inertial sensor but unlike the accelerometer it provides data for angular velocity and orientation of the wearer in X, Y, and Z direction.
LOW LEVEL ACTION RECOGNITION:
The process of recognizing low-level actions such as standing, walking, running, sitting, and so forth through inertial sensors with statistical or machine learning approaches.
SMARTPHONE USAGE:
With the help of screen time out smart phone usage can be calculated.
SOCIAL MEDIA USAGE:
All social media applications reside in the Smartphone therefore their usage data can be computed using I2C protocols.
SELF-REPORTING FOR STRESS:
User need to report their stress level at the time of request.
STROOP TEST:
The Stroop effect is related to selective attention, which is the ability to respond to certain environmental stimuli while ignoring others.
Benefits of the ProjectStress recognition has been carried out extensively either using physiological sensors or with the psychological tests. Although these tests provide us the baseline but conducting them regularly is not feasible. It is better to use these baselines in order to correlate them with the daily activities and the usage of social media on the mobile phones to recognize the stress. In this way, the stress recognition can be carried out in a ubiquitous way through smart phones.
Moreover, stress recognition is quite a subjective study and thus the baselines from people with different region, culture, ethnicity does not provide efficient results and there is no such dataset available for stress recognition which refers to the people of Sindh region, with such culture.
Technical Details of Final Deliverable1.Project will be APK android based Application. This will be deployed in any Android supported device to perform specified task of measuring stress.After the collection of requirement, requirement document will be deliverable
2.Technical design of project documents
3.Project working of application development
4.Project testing and evaluation (working report &testing) .Data collected that can be used for stress and its measuring
5.Project writing
Final Deliverable of the Project Software SystemCore Industry HealthOther Industries IT Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 59000 | |||
| Physilogical sensors | Equipment | 2 | 12000 | 24000 |
| Smart watch | Equipment | 1 | 15000 | 15000 |
| Android phones | Equipment | 1 | 10000 | 10000 |
| Documentation printing & postal | Miscellaneous | 1 | 10000 | 10000 |