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Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

This study aims to examine the associations of collaboration measured as social network characteristics with perceived job demands, job control and social support in primary healthcare professionals.

A cross-sectional study design incorporating social network analysis was utilized. Wellbeing surveys with a network questionnaire were sent to care personnel (physicians, nurses and allied health workers) of Finnish primary healthcare in December 2022 (n = 96). Correlation coefficients and multivariate linear regression modeling were used to analyze the associations.

Higher level of collaboration (measured as number of connections in the network) was associated with lower perceived job demands and higher job control. Care professionals’ frequency of collaboration and proportion of connections with the same occupation (homophily) were borderline associated with social support, indicating further research needs. Larger professional networks, perhaps enabling better teamwork and sharing of workload or information, may directly or indirectly protect from job strain.

Work-related collaboration in primary care should be encouraged and large support networks need to be promoted further. Individuals, especially allied health workers, working in multiple locations or as a sole member of their occupation group in the work community need to be provided with adequate social support.

Social network analysis has been proposed as a tool to investigate care integration and collaboration, but direct analyses of network measures and validated wellbeing instruments have remained absent. This study illuminated the role of collaboration structures in work-related wellbeing of care professionals by showcasing the potential of social network analysis.