• Rugved tatkare
• Gaurang Kalyankar
• Shrawani Dhomne
• Vaibhavi Raje
• Prof. Amit Nerurkar

One of the main forces in our lives, emotions have an impact on many different areas of it. The purpose of this research study is to offer a mood-based API system that analyses and detects an individual's emotional state by taking into account both subjective reactions and physiological data, such as Heart Rate Variability (HRV) and Electrodermal Activity (EDA). The API is made up of components that gather data from wearables, process it on a server, and forecast the outcome for use in web-based apps as plain data. Users can connect with the API and modify the algorithm using the web application. The wearable gadget collects HRV and EDA data over a predetermined period of time. Machine learning modus operandi are then used to evaluate the data and estimate the wearer's emotional state.

Physiological Parameters, ECG, HRV, EDA, GSR

"Mindmeter: Utilizing Physiological Signals for Emotional Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.b140-b147, May-2024, Available :http://www.jetir.org/papers/JETIR2405118.pdf

"Mindmeter: Utilizing Physiological Signals for Emotional Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppb140-b147, May-2024, Available at : http://www.jetir.org/papers/JETIR2405118.pdf