A QUANTITATIVE EVALUATION OF YOGA POSTURES USING IMAGE PROCESSING AND HOTELLING’S T² STATISTICAL ANALYSIS

Pritesh Dineshbhai Gohil — 2026-01-06

The aim of this study is to use computer vision and statistical analysis to measure how yoga practice can improve body posture. A Python-based model was developed that can recognize different yoga poses from images and then create a 3D skeleton of the human body using landmark points. For each pose, twelve important landmarks such as shoulders, elbows, hips, and knees were identified, and angles were calculated to check the correctness of posture. To evaluate whether these landmarks showed improvement after one month of yoga practice, we applied Hotelling’s T² test, a multivariate statistical method that can detect overall changes across several joints at the same time. The results showed that some landmarks had significant differences before and after yoga, meaning that the posture became more aligned and balanced. This method provides an objective way of checking yoga progress instead of relying only on visual observation. The study demonstrates that by combining image processing with statistical testing, it is possible to give meaningful feedback to yoga practitioners, trainers, and even rehabilitation experts in a simple and scientific manner.

ROLE OF VLSI IN MODERN BIOMEDICAL APPLICATIONS

Saima Siddiqui — 2026-01-20

Very Large Scale Integration (VLSI) means integrating a number of transistors in a single chip to create an electronic circuit. It has become the necessity of modern biomedical systems, in which many microprocessors, memory chips and Integrated circuits (ICs) are fabricated for continuous sensing of patient’s health details and for data integration interface in which patient’s data are transferred securely. This review summarizes recent advancements (2021–2025) regarding the role of VLSI circuits in facilitating the entire continuum of patient-centered healthcare, ranging from analog front-ends that capture micro-volt bio signals to edge-AI accelerators that provide on-device diagnosis while ensuring privacy. We organized the application of VLSI circuits in biomedicals like wearable monitoring (ECG/EEG), implantable therapeutics (pacemakers, neuro stimulators), biomedical imaging (ultrasound/X-ray readout SoCs), and neuromorphic/AI-enabled bio signal processing in a table. In modern biomedical applications, VLSI plays three major roles: (1) Miniaturization i.e. fitting a large number of ICs in a single small silicon chip which is easy to wear and implanted inside the body due to its small size. Wearable and Implantable devices are made using these techniques; (2) Reliability i.e. less number of failures and long-term usage; (3) Low power consumption by using low power VLSI design. This review paper gives an overview of evolution of VLSI in biomedical engineering, wearables and implantable devices integration, Imaging, neuromorphic and AI enabled VLSI system and at last some challenges that we face for low power VLSI design and its principles. In future, Biomedical, VLSI and AI engineers if combined together can give rise to many advancements in the clinical needs by scaling it with limited resources while keeping in mind that cost should also be low. The whole healthcare system should make a strategic tool for making biomedical devices less costly, safer, more accurate, and easier to use for patients and it can only possible by combining VLSI and AI in it.

International Journal of Engineering Science Technologies

A QUANTITATIVE EVALUATION OF YOGA POSTURES USING IMAGE PROCESSING AND HOTELLING’S T² STATISTICAL ANALYSIS

ROLE OF VLSI IN MODERN BIOMEDICAL APPLICATIONS