August 28, 2013Elektronika ir ElektrotechnikaOpen Access

Multiple Physiological Signal-Based Human Stress Identification Using Non-Linear Classifiers

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Population

40 healthy subjects aged 20-25 years, with similar educational and cultural backgrounds, free from history…

Comparison

Mental arithmetic task with audio distraction to… vs Normal/relaxed state (initial relaxation period).

Design

Other

Follow-up

66 minutes (duration of the task protocol)

Authors

MMM. MurugappanVels University SYSazali YaacobIntel (Malaysia)

Discussion

Member takes

Implication

May support lab-based acute stress detection via HRV; leaves open clinical validation and real-world utility.

Structured PICO

Population

40 healthy subjects (20 males, 20 females) aged 20-25 years, with similar educational and cultural backgrounds, free from history of medication, drug intake, and smoking.

Intervention

Mental arithmetic task with audio distraction to induce stress, with physiological signals (ECG, EMG, HRV, GSR, ST) recorded and analyzed using K-Nearest Neighbour (KNN) and Probabilistic Neural Network (PNN) classifiers.

Comparator

Normal/relaxed state (initial relaxation period).

Outcome

Classification accuracy of stress versus normal states.surrogate

Higher-order statistical features of heart rate variability can accurately classify acute mental stress induced by arithmetic tasks.

Cite This Study

Murugappan et al. (2013) studied this question.

synapsesocial.com/papers/6a7f0fa573b39cefb3f007c5 https://doi.org/10.5755/j01.eee.19.7.2232

View Full Paper

Ask AI

Bookmark

Multiple Physiological Signal-Based Human Stress Identification Using Non-Linear Classifiers

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Multiple Physiological Signal-Based Human Stress Identification Using Non-Linear Classifiers

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider