Abstract— Nature may be used as a treatment method for patients with mental disorders which has yet to
be implemented despite numerous evidence showing that being in touch with nature links to increased
happiness, positive affect, positive social interactions, and a sense of meaning and purpose in life, as well
as reduced mental distress. This project focuses on demonstrating the benefits of nature towards improving
emotional well-being of people based on the detection of Electrodermal Activity (EDA). EDA signals will
be collected from the controlled and experimental participants for the identification of nature’s positive
impact towards participants’ mental well-being. Raw signals will require pre-processing and feature
extraction which will use an open-source Python toolkit called PyEDA. The project will also incorporate
machine learning for EDA signal classification which also utilizes python open-source software. The
results will be observed and studied based on its accuracy in classifying the EDA signals between the
controlled and experimental conditions. This project will be heading towards improving mental health
treatment by proving that incorporating the world’s most abundant resources, nature together with the
incorporation of biosensors for mental health detection will help close the gap between mental health
patients and clinicians
