A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults.

Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.

A standard set of outcome measures for the comprehensive assessment of osteogenesis imperfecta.

BACKGROUND: Osteogenesis Imperfecta (OI) is a genetic disorder also known as 'brittle bone disease'. The clinical manifestation of OI shows a wide variation. Therefore, care for patients with OI requires an interdisciplinary approach. The effectiveness of particular interventions and treatment protocols of interdisciplinary teams is not clear due to a non-standardized and wide variation of patient outcomes thus making the comparison of outcome measures available in the literature difficult. It is only by agreeing on a common, standard set of outcome measures for the comprehensive appraisal of OI that comparisons across interdisciplinary treatment centers for OI will be possible in the future. METHODS: The Key4OI international interdisciplinary working group of 27 members used a consensus-driven modified Delphi approach to develop a set of global outcome measures for patients with OI. The International Classification of Functioning, Disability and Health (ICF), was used to define domains and organize the outcomes from the literature search. After reviewing the outcomes extracted from the literature, trials and registries, the working group agreed on a final selection of domains and their definition (ICF definition as well as a lay description). These domains were then presented to the focus groups who prioritized the outcome domains by taking into account the items important to the OI community. All content was collected and analyzed and final domains were determined. A consensus of appropriate measuring instruments for each domain was reached with Delphi rounds. The entire approach was in line with the International Consortium for Health Outcomes Measurement ICHOM methodology. RESULTS: More than 400 different outcome measures were identified in our literature search. After three Delphi rounds, 24 domains were selected. After the focus group sessions, the number of domains were reduced to 15. A consensus was reached on the measuring instruments to cover these domains for both children and adults. CONCLUSION: The Key4OI project resulted in standard set of outcome measures focused on the needs and wishes of individuals with OI and their families. This outcome set will enable healthcare teams and systems to compare and to improve their care pathways and quality of care worldwide. Further studies are needed to evaluate the implementation of this standardized outcome set.