Polar flow app

The Polar Ignite, the second multisport activity tracker (Polar Electro Oy, 2022; Kempele, Finland) (ID 5D935A29, firmware 2.0.25), uses similar sensors to the Garmin device. The tracker is also able to detect sleep stages such as awake time and light, deep and REM sleep time, as well as the normal sleep/wake patterns TIB, TST, Awake, SOL and WASO. For further detailed sleep analysis, the raw data were automatically transferred to the Polar data cloud. Polar uses the “Nightly Recharge System” as a proprietary algorithm. All analyzed data were displayed in the Polar Flow app. In addition to the hypnogram, three further diagrams were displayed, HRV (RMSSD), beat to beat measurement and the respiratory rate data. The respiratory rate was calculated according to the same principle as the Garmin device, explained in Section 1. The measurement detection was restricted to the first four consecutive hours of sleep detection during sleep. In addition, no SpO₂ data were calculated or reported in the spreadsheet report of the Polar Flow app [72 ].

All rowers wore a multisensory smartwatch allowing to measure heart rate (HR) at 1 Hz via optical heart rate measurement technology at the wrist and with a chest belt. Off-training heart rate was recorded with the optical wrist sensor. All training sessions were recorded with the chest belt, to avoid inaccurate measurements especially during rowing related to muscular contraction of the arm muscles. Participants were asked to label all periods of scheduled training in the smartwatch settings with the appropriate activity (e.g., rowing, cycling, running) and select the label other indoor activity for off-training heart rate recording. The setting other indoor activity allows sampling of heart rate at 1 Hz throughout off-training without activation of GPS, ensuring longer operational time. All athletes were instructed to upload their data at least once per week via the Polar Flow App (Polar, Oy, Finland) to the cloud-based Polar Flow software. Afterwards, all data were extracted as TCX files from each rower’s Polar Flow dashboards. The TCX files were parsed with the ElementTree XML API of the Python programming language (3.8) and stored in a MongoDB instance. Preprocessing and data analysis were conducted with the Python data analysis library Pandas (v.1.0.3).