Key result
A proposed portable IoT-based pulse acquisition system combining Ayurvedic Nadi Nidan principles with machine learning algorithms offers a promising non-invasive approach for predicting cardiovascular disease risk.
Why the study?
Nadi Nidan requires extensively trained practitioners to diagnose illness from pulse readings, and pulse signal analysis remains in its infancy.
Combining ancient Ayurvedic Nadi Nidan techniques with modern IoT pulse acquisition and machine learning may offer a novel, non-invasive approach for predicting cardiovascular disease risk.
Originating in ancient Ayurveda, the Nadi Tantra or Nadi Nidan technique is a valid and useful method for identifying bodily imbalances.The word "Nadi" or "pulse" describes a vital energy flow that passes through the human body's delicate medium and enables doctors, or Nadi Vaidyas, to feel and comprehend the flow of blood through the heart.Nadi Nidan is an ancient Ayurvedic technique that uses pulse pressure to detect various ailments as well as an imbalance of the body's physical, mental and emotional systems.But in order to diagnose any illness, Nadi Tantra needs practitioners with extensive training and the ability to read people's pulses.OBJECTIVES: This paper will describe the IoT-based pulse acquisition system for measuring Tridoshas (namely Kapha, Pitta and Vatta) and the machine learning algorithms utilized to train the model based on Nadi Nidan principles for heart disease prediction. METHODS:We apply visualization and analytic techniques from dynamical systems, chaotic attractors, and pattern recognition to this aim.We adhere to the standard data analysis approach since pulse signal analysis is still in its infancy. RESULTS:Using a few key traits, it is possible to predict the severity of heart problems and perhaps save lives.Neural networks and linear regression are only two examples of the many machine learning and deep learning methods that may be used to assess medical parameters for this goal.CONCLUSION: This literature review makes use of secondary data gathered from various sources.The knowledge gained will help to understand the many types of heart disease and cardiovascular disorders and evaluate the latest advancements in the prediction of these disorders through the use of Nadi Nidan and Machine Learning techniques.It is possible to design a new or enhanced model for predicting a person's risk of heart disease using this information.
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A 2024 study conducted a review in Cardiovascular Diseases. IoT-based portable pulse acquisition system (Nadi Nidan) was evaluated. A proposed portable IoT-based pulse acquisition system combining Ayurvedic Nadi Nidan principles with machine learning algorithms offers a promising non-invasive approach for predicting cardiovascular disease risk.
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