The Role of Multi-Sensor Measurement in the Assessment of Movement Quality: A Systematic Review.

BACKGROUND: Movement quality is typically assessed by drawing comparisons against predetermined movement standards. Movements are often discretely scored or labelled against pre-set criteria, though movement quality can also be evaluated using motion-related measurements (e.g., spatio-temporal parameters and kinematic variables). Wearable technology has the potential to measure and assess movement quality and offer valuable, practical feedback. OBJECTIVES: A systematic approach was taken to examine the benefits associated with multi-sensor and multiple wearable-device usage, compared with unimodal applications, when assessing movement quality. Consequently, this review considers the additional variables and features that could be obtained through multi-sensor devices for use in movement analyses. Processing methods and applications of the various configurations were also explored. METHODS: Articles were included within this review if they were written in English, specifically studied the use of wearable sensors to assess movement quality, and were published between January 2010 and December 2022. Of the 62,635 articles initially identified, 27 papers were included in this review. The quality of included studies was determined using a modified Downs and Black checklist, with 24/27 high quality. RESULTS: Fifteen of the 27 included studies used a classification approach, 11 used a measurement approach, and one used both methods. Accelerometers featured in all 27 studies, in isolation (n = 5), with a gyroscope (n = 9), or with both a gyroscope and a magnetometer (n = 13). Sampling frequencies across all studies ranged from 50 to 200 Hz. The most common classification methods were traditional feature-based classifiers (n = 5) and support vector machines (SVM; n = 5). Sensor fusion featured in six of the 16 classification studies and nine of the 12 measurement studies, with the Madgwick algorithm most prevalent (n = 7). CONCLUSIONS: This systematic review highlights the differences between the applications and processing methods associated with the use of unimodal and multi-sensor wearable devices when assessing movement quality. Further, the use of multiple devices appears to increase the feasibility of effectively assessing holistic movements, while multi-sensor devices offer the ability to obtain more output metrics.

Moving Forward: Understanding Correlates of Physical Activity and Sedentary Behaviour during COVID-19 in Children and Adolescents-An Integrative Review and Socioecological Approach.

Novel coronavirus disease 2019 (COVID-19) pandemic restrictions have negatively impacted physical activity (PA) and sedentary time/behaviour. This integrative review systematically explored the socioecological factors that impacted and influenced these movement behaviours in children and adolescents during the pandemic. Five electronic databases were systematically searched in January 2021, with data extracted from 16 articles (n = 18,352; 5-17 years; 12 countries). Risk-of-bias was assessed using the Mixed Methods Assessment Tool (MMAT), with correlates identified, coded, and themed via thematic analysis. A socioecological model of during-pandemic PA and sedentary time/behaviour was conceptualised and mapped to the Capability, Opportunity, Motivation, and Behaviour (COM-B) model of behaviour-change mechanisms, illustrating influences over five levels: Individual (biological)-age and sex; Individual (psychological)-mental health, and cognition, motivation, and behaviour; Social-family factors, and structured support; Environmental-area of residence and resources; and Policy-COVID-19-related rules. For sedentary time/behaviour, individual-(age and sex), social-(family factors) and policy-(COVID-19-related rules) level factors may be important correlates. There were no age or sex associations with PA levels, though there was some indication that sedentary time/behaviour increased with age. Interventions seeking to enhance young people's movement behaviours during periods of enforced restrictions should focus on enhancing opportunities on a social and environmental level.

Moving Forward: Understanding Correlates of Physical Activity and Sedentary Behaviour during COVID-19-An Integrative Review and Socioecological Approach.

Population-level physical activity (PA) and sedentary time/behaviour estimates represent a significant public health issue exacerbated by restrictions enforced to control COVID-19. This integrative review interrogated available literature to explore the pandemic's impact on correlates of such behaviours in adults (≥18 years). Five electronic databases were systematically searched in January 2021. Data extracted from 64 articles were assessed for risk-of-bias using the Mixed Methods Assessment Tool, with correlates identified, coded, and themed via thematic analysis. A socioecological model of during-pandemic PA was conceptualized and mapped to the Capability, Opportunity, Motivation, and Behaviour (COM-B) model of behaviour change mechanisms, which illustrates influences over five levels: Individual (biological)-general health; Individual (psychological)-mental health, cognition, motivation, and behaviour; Social-domestic situation, sociodemographic factors, support, and lifestyle choices; Environmental-resources and area of residence; and Policy-COVID-19-related rules. For sedentary time/behaviour, individual level factors, namely general and mental health, may be important correlates. Neither age or sex were clearly correlated with either behaviour. As we transition into a new normal, understanding which behaviour mechanisms could effectively challenge physical inactivity is essential. Targeting capability on a psychological level may facilitate PA and limit sedentary time/behaviour, whereas, on a physical level, maximizing PA opportunities could be crucial.