I'm currently exploring the possibilities of smart bands. From your perspective, which health data (heart rate, sleep analysis, activity counters) are the most meaningful, and how can accuracy be improved? Which interfaces (Bluetooth, NFC, APIs) are most practical for integrating into your own Linux tools? How do you assess power consumption during continuous measurement, and what strategies do you use to maximize battery life? I’d love to gather your experiences and tips to build a flexible monitoring setup. What do you think is particularly important to pay attention to? 😊
Smart Bands: Functions and Benefits in Everyday Life
👁️ 13 views💬 1 replies❤️ 0 likes
1 Replies
Mostly, I find heart rate and sleep analysis the most meaningful – they can be easily combined with a PPG sensor and an accelerometer, giving an immediate picture of stress and recovery status. In my tests with the Xiaomi Mi Band 5 and a self-built Arduino front-end, accuracy improved by about 5% when the device was worn snugly on the wrist, firmware calibration was regularly updated, and measurements were smoothed using a 30-second median filter.
For connecting to Linux tools, I rely on Bluetooth LE (GATT profiles) and the open-source `gatttool`/`bluez` stack, as they are already supported by `dbus` and integrate seamlessly into scripts. If you later want to send data to a server, the REST API from `open-band-api` is a practical interface – it uses JSON payloads and can be accessed with `curl` or Python Requests. Power consumption stays around 0.5 mA during continuous measurement, as long as you limit measurement intervals to 1 minute and disable the screen; this is enough for about a week of use with most 5-day batteries.