SolareSkin: Self-powered visible light sensing through a solar cell e-skin

SolareSkin is a self-powered and ubiquitous electronic skin equipped with ultraflexible organic solar cells for visible light sensing and energy harvesting. This dual-functional system captures light signals, transforms them into electrical impulses and enables multi-class gesture and activity recognition. Its design employs a photocurrent model that allows solar cells to serve as energy harvesters and visible light sensors simultaneously. The solar cells demonstrate a decent conversion rate of incident light into electricity, supporting an efficient, sustainable operation. Additionally, the system incorporates advanced system integration with a low-powered data collection board embedded with wireless transmission modules and an intuitive user interface. An algorithm is employed for signal analysis with data pre-processing methods and several machine learning models. The data pre-processing methods comprise filtering, scaling, normalization, segmentation, and downsampling of raw sensor data to reduce noise and increase prediction accuracy. The machine learning model evaluation focuses on three algorithms: Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Random Forest, due to their efficiency with high-dimensional, nonlinear data. The experimental results suggest the excellent performance of SVM in recognizing 7-class finger gestures and 7-class body activities, with accuracies of 97.3% and 96.7%, respectively. This advancement in electronic skin technology is promising for ubiquitous human-centric sensing, enabling various applications such as healthcare monitoring, human-computer interaction, and smart homes.