A novel optoelectronic synapse compatible with existing chip technology is demonstrated, capable of mimicking memory and learning functions using light, ideal for future neuromorphic computing in biomedicine. The device can switch between short-term and long-term memory states using light pulses, and experiments on real-world biomedical data (EEG, EMG, ECG) showed significant improvement in classification accuracy. The optical programming property enables ultralow power fine-tuning and solutions for patient-specific issues in edge computing scenarios. The device exhibits impressive light-sensitive characteristics, enabling light-triggered synaptic functions, making it promising for neuromorphic vision applications. A 5×5 optoelectronic synapse array is developed, effectively simulating human visual perception and memory functions. The flexible optoelectronic synapse holds potential for advancing neuromorphic physiological signal processing and artificial visual systems in wearable applications. The device is fabricated on a 4-inch Si wafer, with a 10×10 μm² cell size. It demonstrates bipolar resistive switching behavior, high AC endurance, and synaptic functions such as long-term potentiation (LTP), long-term depression (LTD), short-term plasticity (STP), and paired-pulse facilitation (PPF). The device also exhibits photo-synaptic current (PSC), photonic PPF, short-term memory (STM), long-term memory (LTM), and learning-forgetting-relearning processes. The device maintains consistent performance under bending conditions, demonstrating robust stability and reliability. The optoelectronic memristive device can transform its PSC response from STM to LTM by manipulating light intensity or exposure time. The device is capable of visual memory retention, with memory strength increasing with more stimuli and longer decay times for forgetting. The device can be used for ECG-based arrhythmia detection, showing improved classification accuracy after fine-tuning. The device's light-responsive features make it suitable for artificial visual perception and wearable applications. The study highlights the potential of the optoelectronic memristive synapse for neuromorphic computing and biomedical applications.A novel optoelectronic synapse compatible with existing chip technology is demonstrated, capable of mimicking memory and learning functions using light, ideal for future neuromorphic computing in biomedicine. The device can switch between short-term and long-term memory states using light pulses, and experiments on real-world biomedical data (EEG, EMG, ECG) showed significant improvement in classification accuracy. The optical programming property enables ultralow power fine-tuning and solutions for patient-specific issues in edge computing scenarios. The device exhibits impressive light-sensitive characteristics, enabling light-triggered synaptic functions, making it promising for neuromorphic vision applications. A 5×5 optoelectronic synapse array is developed, effectively simulating human visual perception and memory functions. The flexible optoelectronic synapse holds potential for advancing neuromorphic physiological signal processing and artificial visual systems in wearable applications. The device is fabricated on a 4-inch Si wafer, with a 10×10 μm² cell size. It demonstrates bipolar resistive switching behavior, high AC endurance, and synaptic functions such as long-term potentiation (LTP), long-term depression (LTD), short-term plasticity (STP), and paired-pulse facilitation (PPF). The device also exhibits photo-synaptic current (PSC), photonic PPF, short-term memory (STM), long-term memory (LTM), and learning-forgetting-relearning processes. The device maintains consistent performance under bending conditions, demonstrating robust stability and reliability. The optoelectronic memristive device can transform its PSC response from STM to LTM by manipulating light intensity or exposure time. The device is capable of visual memory retention, with memory strength increasing with more stimuli and longer decay times for forgetting. The device can be used for ECG-based arrhythmia detection, showing improved classification accuracy after fine-tuning. The device's light-responsive features make it suitable for artificial visual perception and wearable applications. The study highlights the potential of the optoelectronic memristive synapse for neuromorphic computing and biomedical applications.