Are you stressed'? Quantifying stress levels from physiological and body-movement signals

Project Title

Are you stressed'? Quantifying stress levels from physiological and body-movement signals

Project Area of Specialization Internet of ThingsProject Summary

Stress is defined as the non-specific response of the human body to any demand put forth onto the body.Feeling of stress and anxiety is a part of life.Some level of stress can be good for us,but in some situations they can become a burden or even a health risk. It is well known that stress manifests as changes in physiological signals such as heartbeat, respiration, skin conductance etc. Furthermore, it is also known that stress can affect motor functions of a human being. For example, an individual may respond to stressful situation by becoming proactive whereas another individual may respond to such situation by becoming passive.

So our project is to analyze the state of stress for each subject.We are going to to develop a low-cost module based on wearable sensors, which can measure various physiological as well as body-movement signal in order to predict the state of stress for each subject. We are integrating different sensors into an Internet of Things framework through which data can be recorded seamlessly.After this we train machine learning models for classifying between individuals in state of high-stress and low-stress based on the data acquired from experiments.

The system block diagram is proposed in figure 1:

Fig.1

Project Objectives

The main objective of this project is to develop a low-cost module based on wearable sensors which can be used to estimate the state of stress for individuals.

The key project objectives are stated here:

1. To understand (and appreciate the importance of) ethical guidelines for pursuing projects related to data acquisition from human subjects
2. To develop an understanding of the relationship between stress and physiological/body movement signals
3. To conduct a literature survey and shortlist physiological signals for use in experiments
4. To acquire sensors for shortlisted physiological signals and body movement and build a prototype for data acquisition (based on either Arduino or Raspberry Pi)
5. To develop an experiment plan
6. To acquire physiological and body movement signals as per planned experiments
7. To train machine learning models for classifying between individuals in state of high-stress and low-stress based on the data acquired from experiments.

Project Implementation Method

Step:1 Building of a prototype:

 Firstly, we are going  to build a prototype based on wearable sensors that includes heart rate sensors , oxygen saturation level sensors , galvanic sensors etc for measuring of stress levels in human subjects.

Step:2 Collection of data:

After building of protoype we will collect data from human subjects in coordination with the TL dept. Ethics Committee. The volunteer participants will be informed about the purpose and the procedure of the study.

Step:3 Data Consolidation:

After collection of different data, data consolidation will be  employed  between different data types collected from different sensors for the classification and processing of data.

Step:4 Machine Learning:

The Machine learning will be used on the data acquired for experiment for classifying between different state of stress levels.

Benefits of the Project

According to the American Psychological Association, stress is linked to the six leading causes of death: heart disease, cancer, lung ailments, accidents, cirrhosis of the liver and suicide. And more than 75 percent of all physician office visits are for stress-related ailments and complaints. we can save thousands of life just by quantifying the stress level among people .

• In hospitals, with the help of this, patients will be care with more effective monitoring.
• We can use at places other than hospitals and having confidence of applying such techniques without physician intervention
•  We can help those people with disabilities like blind or any paralyze patients.

Technical Details of Final Deliverable

The prototype will be delivered along with its technical detailed reports;

• A wearable device with diferent physiological sensors capable to measure heart rate, temperature and other sensors which can be used to estimate the state of stress for individuals.
• And with the use of machine learning algoithms we are going to divide stress in 3 levels low stress,medium stress, high stress through which we can figure it out that at which position a certain person limits .

Final Deliverable of the Project Hardware SystemCore Industry HealthOther Industries Health Core Technology Internet of Things (IoT)Other Technologies Wearables and ImplantablesSustainable 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)	79891
Esp32 IOT development board	Equipment	6	1559	9354
MAX30102 Heart rate sensors	Equipment	6	550	3300
9-Axis MPU9250 Accelerometer	Equipment	5	750	3750
Myoware muscle sensor	Equipment	5	5860	29300
Thermistors	Equipment	6	90	540
16x2 Character LCD Module Blue Background	Equipment	5	250	1250
SD Card Module	Equipment	6	100	600
DS3231 Precision RTC Real Time Clock Module	Equipment	5	230	1150
USBASP AVR MICROCONTROLLER PROGRAMMER	Equipment	5	250	1250
Pulse rate sensor	Equipment	6	750	4500
DHT11 Temperature sensor	Equipment	6	140	840
Skin Conductance sensor	Equipment	6	2347	14082
Breadboard	Miscellaneous	5	200	1000
40P Male to Male Jumper Wire Cable for Arduino	Miscellaneous	5	125	625
40P Male to Female Jumper Wire Cable for Arduino	Miscellaneous	5	125	625
9V Batteries	Miscellaneous	10	85	850
disposable surface electrodes	Miscellaneous	50	40	2000
Type-C cable	Miscellaneous	5	400	2000
32Gb-Micro Sd Card	Miscellaneous	5	575	2875