The relationship between forward head posture and cervical muscle performance in healthy individuals

Background Forward head postures (FHP) are proposed to adversely load cervical spine structures. Neck muscles provide support for the neck, and thus an imbalance in neck muscle performance could potentially contribute to the development of FHP. Previous studies have not considered the interaction of multiple muscle groups with regard to postural orientation. Given the interdependence of muscles along the cervical spine for optimal orientation and physical support of the vertebral column, the performance of a single muscle group may not accurately reflect the coordinated ability of the muscles to maintain a neutral neck posture. Purpose The purpose of this study was to investigate the relationship between FHP and the balance between the cervical extensor and flexor muscle groups in healthy individuals. We hypothesised that the magnitude of FHP would be associated with the strength and endurance performance ratios between the cervical extensor and flexor muscle groups. Methods Twenty male and 24 female volunteers were photographed in the sagittal plane wearing surface markers. The FHP of each participant was measured via the tragus-sternum marker distance over two conditions: (1)in relaxed standing and (2)during a sustained sitting task. Maximal strength (Nm) and endurance (s) performance of the extensor and flexor muscle groups were recorded at the upper (craniocervical flexion/extension (CCF/CCE)) and lower (cervicothoracic flexion/extension (CTF/CTE)) cervical regions. Muscle performance measures were expressed as extension:flexion ratios and their relation to FHP evaluated. A stepwise multiple regression analysis using backward elimination was utilised to examine the relationship between the postural measures and the muscle performance ratio measures. Separate models were used for the two different postural conditions (standing, sustained sitting). Gender was included as a constant correction factor in all regression models. Where gender was a significant variable in the model, analyses were repeated separately for males and females. Results Greater FHP in standing was significantly associated with reduced proportional CTE to CCF strength in females (R2 = 0.21, P = 0.03) and greater proportional CTE to CTF strength in males (R2 = 0.23, P = 0.03). A greater drift into FHP during sustained sitting was associated with a relative reduction in CCE endurance proportional to CTF endurance in females only (R2 = 0.27, P = 0.017). Conclusion(s) This initial study indicates that the balance in performance between the cervical flexor and extensor muscle groups may impact FHP in healthy individuals. However, the findings were inconsistent across different muscle performance ratios and gender. Larger scale studies are therefore now needed to further clarify the relationship between FHP and muscle performance. Implications The findings suggest that relative performance of the various cervical muscle groups needs to be accounted for when considering postural correction strategies in the clinical setting, as is often recommended.

Detecting drift from event streams of unpredictable business processes

Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.