lm What open source system that could be used on a headles s device is closest to the goal of detecting early signs of a panic attack? INFO:openai:message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=23086 request_id=0e498ac730716e44267081f02de54238 response_code=200 INFO:completion_logger:Logged https://arweave.net/fQfWZ-eEZY-q2AUvK_zEaODTE_cUM9pMUSkZaKso2t0#minblockheight=1194425&minblockhash=JSJUmpAFXtu8aPcukyfUdejBqLYoPS5eKcWcJmKRABrDjDiZ2HFrgMHLATmmmNP- The open-source system closest to the goal of detecting early signs of a panic attack on a headless device would be a combination of machine learning algorithms and physiological sensors. One such example is the use of Heart Rate Variability (HRV) analysis, which can be an indicator of stress and anxiety levels. There are open-source libraries available for HRV analysis, such as the Python-based library called "HeartPy" (https://github.com/paulvangentcom/heartrate_analysis_python). This library can be used to process data from heart rate sensors and analyze HRV, potentially detecting early signs of a panic attack. To implement this on a headless device, you would need to connect the device to a heart rate sensor (e.g., a chest strap or wrist-based sensor) and use the HeartPy library to process and analyze the data in real-time. You could then set up alerts or notifications based on the analysis results to provide early warnings of potential panic attacks.