Comparison of Fitness Tracking Using Three Different Smartwatches during Free Activities in Daily Life

Background: Young women of reproductive age experience various physiological changes, which they measure and track using various devices, including fitness trackers and smartwatches. However, fitness tracking assessment methods are ambiguous because they may differ from model to model. Objective: This study aimed to compare the stress level, heart rate, sleep time, number of steps, and distance traveled, which were calculated using fitness tracking methods for daily-life free activity installed in various smartwatches. Materials and Methodology: Healthy women in their 20s to 30s were recruited for this study, which was conducted from December 2021 to June 2022. The finalized participants wore three different smartwatch models (Mi smartband 6, vivosmart®4, and Band 6) simultaneously on their person for 48 hours and performed their daily activities and recorded them on an hour-based activity chart. Each smartwatch’s measured data (e.g., age, height, weight, and oral medications) were extracted into five datasets: heart rate, stress level, number of steps, distance, and sleep time. Data analyses were conducted using Spearman’s rank correlation coefficient ρ (for comparing heart rates) and Bland-Altman plots (for assessing heart rate agreement). The smartwatches’ fitness trackers were compared using the mean absolute percentage error. Results: The correlation coefficient showed that vivosmart®4 and Band 6 had a higher heart rate agreement (ρ = 0.684). The Bland-Altman plots showed high agreement between Band 6, Mi smartband 6, and vivosmart®4. The heart rate measurement method used under free movement was found to be consistent. The examined smartwatches were able to measure heart rate at the same level even under daily-life free movements. Conclusion: Several different smartwatches’ calculated measured values for heart rate had a high agreement. The smartwatches provided accurate heart rate measurements under daily-life free movement conditions. Furthermore, the calculation methods for stress level were found to differ in the fitness tracking of all the smartwatches. .

BESⅢ track fitting algorithm

A track fitting algorithm based on the Kalman filter method has been developed for BESⅢ of BEPCⅡ. The effects of multiple scattering and energy loss when the charged particles go through the detector, non-uniformity of magnetic field （NUMF） and wire sag, etc., have been carefully handled. This algorithm works well and the performance satisfies the physical requirements tested by the simulation data.

Adaptive multitrack reconstruction for particle trajectories based on fuzzy c-regression models

In this paper, an approach to straight and circle track reconstruction is presented, which is suitable for particle trajectories in an homogenous magnetic field （or 0 T） or Cherenkov rings. The method is based on fllzzy c-regression models, where the number of the models stands for the track number. The approximate number of tracks and a rough evaluation of the track parameters given by Hough transform are used to initiate the fuzzy c-regression models. The technique effectively represents a merger between track candidates finding and parameters fitting. The performance of this approach is tested by some simulated data under various scenarios. Results show that this technique is robust and could provide very accurate results efficiently.