A Novel Smart Belt for Anxiety Detection, Classification, and Reduction Using IIoMT on Students’ Cardiac Signal and MSY

Abstract

The prevalence of anxiety among university students is increasing, resulting in the negative impact on their academic and social (behavioral and emotional) development. In order for students to have competitive academic performance, the cognitive function should be strengthened by detecting and handling anxiety. Over a period of 6 weeks, this study examined how to detect anxiety and how Mano Shakti Yoga (MSY) helps reduce anxiety. Relying on cardiac signals, this study follows an integrated detection-estimation-reduction framework for anxiety using the Intelligent Internet of Medical Things (IIoMT) and MSY. IIoMT is the integration of Internet of Medical Things (wearable smart belt) and machine learning algorithms (Decision Tree (DT), Random Forest (RF), and AdaBoost (AB)). Sixty-six eligible students were selected as experiencing anxiety detected based on the results of self-rating anxiety scale (SAS) questionnaire and a smart belt. Then, the students were divided randomly into two groups: experimental and control. The experimental group followed an MSY intervention for one hour twice a week, while the control group followed their own daily routine. Machine learning algorithms are used to analyze the data obtained from the smart belt. MSY is an alternative improvement for the immune system that helps reduce anxiety. All the results illustrate that the experimental group reduced anxiety with a significant (p < 0.05) difference in group × time interaction compared to the control group. The intelligent techniques achieved maximum accuracy of 80% on using RF algorithm. Thus, students can practice MSY and concentrate on their objectives by improving their intelligence, attention, and memory.

Yoga Meets Intelligent Internet of Things: Recent Challenges and Future Directions

“…Wearable devices are considered a better approach for monitoring and detecting yoga positions. Pal et al [ 15 ] used a smart belt to analyze the performance of yoga. Pauranik and Kanthi [ 85 ] designed wearable devices to monitor heart rate, yogic breathing, and posture.…”

“…Additionally, to address the demand of professionals who want to practice at home, the integration of IoT provides them with potential solutions, where multiple intelligent yoga mats [ 12 ], wearable devices [ 13 ], and yoga-posture recognition sensors [ 14 ] are designed to monitor, detect, and provide feedback when mistakes happen. For instance, wearable sensors or Kinect/RGB camera-based yoga posture recognition and a correction approach are deployed in [ 15 ]. However, this approach possesses privacy issues, which are addressed in [ 14 , 16 ], which undergoes the detection of yoga postures using IoT, infrared sensors, and intelligent techniques.…”

Therapeutic Efficacy of a Formulation Prepared with Linum usitatissimum L., Plantago ovata Forssk., and Honey on Uncomplicated Pelvic Inflammatory Disease Analyzed with Machine Learning Techniques

“…Hence, we evaluated and compared the efficacy of the vaginal application of a formulation prepared with L. usitatissimum , P. ovata , and honey [ 12 ] on uPID with standard drugs, doxycycline, and metronidazole. In addition, we also used the same machine learning models [ 49 , 50 , 51 , 52 , 53 , 54 ] including Decision Tree (DT) [ 55 , 56 , 57 ], Random Forest (RF) [ 58 , 59 ], Logistic Regression (LR), and AdaBoost (AB) with three cross-validation models including 2-fold, 5-fold, and 10-fold to classify the standard and pessary groups. The main contributions of this study are given below: The pessary of psyllium and linseed with honey is beneficial for PID but has not been validated to date.…”

A Hybrid Stacked Restricted Boltzmann Machine with Sobel Directional Patterns for Melanoma Prediction in Colored Skin Images

“…Artificial intelligence (AI) and associated technologies are starting to be adopted by healthcare organizations as they become increasingly widespread in the industrial and medical sectors [ 20 , 21 , 22 , 23 , 24 ]. Studies [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ] have proven that AI is as good as, or better than, human doctors when it comes to medical diagnosis.…”