A ResNet50 trained on mel-spectrograms of basil plant voltages reportedly reaches 97% accuracy in a seven-emotion classification, yet the same table shows near-zero recall for three emotions and a macro F1 of 0.56.
Recognizing Individuals and Their Emotions Using Plants as Bio-Sensors through Electro-static Discharge
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abstract
By measuring the electrostatic discharge of human bodies together with Mimosa Pudica and other plants in response to the human movement, we have been able to recognize (a) individuals based on their distinctive pattern of body movements with 66% accuracy as well as (b) positive or negative mood based on their gait characteristics with 85% accuracy. We use the Plant SpikerBox, a device that measures the electrical action potential while also measuring the electrostatic discharge between the electrode on the leaves of a plant and the capacitively coupled human body.
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q-bio.OT 1years
2025 1verdicts
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citing papers explorer
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Plant Bioelectric Early Warning Systems: A Five-Year Investigation into Human-Plant Electromagnetic Communication
A ResNet50 trained on mel-spectrograms of basil plant voltages reportedly reaches 97% accuracy in a seven-emotion classification, yet the same table shows near-zero recall for three emotions and a macro F1 of 0.56.