Daily-Life Walking Speed, Quality and Quantity Derived from a Wrist Motion Sensor: Large-Scale Normative Data for Middle-Aged and Older Adults.

Walking is crucial for independence and quality of life. This study leverages wrist-worn sensor data from UK Biobank participants to establish normative daily-life walking data, stratified by age and sex, to provide benchmarks for research and clinical practice. The Watch Walk digital biomarkers were developed, validated, and applied to 92,022 participants aged 45-79 who wore a wrist sensor for at least three days.

A Wrist-Worn Wearable Device Can Identify Frailty in Middle-Aged and Older Adults: The UK Biobank Study.

Objectives: Digital gait biomarkers collected from body-worn devices can remotely and continuously collect movement types, quantity, and quality in real life. This study assessed whether digital gait biomarkers from a wrist-worn device could identify people with frailty in a large sample of middle-aged and older adults.

Design: Cross-sectional study.

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device.

Objective: Freezing of Gait (FOG) is prevalent in people with Parkinson's disease (PD) and severely disrupts mobility. Detecting the exact boundaries of FOG episodes may facilitate new technologies in "breaking" FOG in real-time. This study investigates the performance of automatic device-based FOG detection.

Poor mobility and lower limb weakness are associated with three distinct depressive symptom trajectories over 6 years in older people.

Objectives: Physical decline can be associated with the onset of depressive symptoms in later life. This study aimed to identify physical and lifestyle risk factors for depressive symptom trajectories in community-dwelling older adults.

Methods: Participants were 553 people aged 70-90 years who underwent baseline physical, psychological and lifestyle assessments.

Is Maximal or Usual Walking Speed from Large Scale Wrist Sensor Data Better at Predicting Dementia, Depression and Death?

Older people are at increased risk of many adverse health outcomes, including dementia and depression, that burden the global health system. This paper presents algorithms for the large-scale assessment of daily walking speeds. We hypothesize that (i) data from wrist-worn sensors can be used to assess walking speed accurately; and that (ii) maximal daily walking speed is a better predictor of health outcomes than usual daily walking speed.

Prediction of injurious falls in older adults using digital gait biomarkers extracted from large-scale wrist sensor data.

Objectives: To determine whether digital gait biomarkers captured by a wrist-worn device can predict injurious falls in older people and to develop a multivariable injurious fall prediction model.

Design: Population-based longitudinal cohort study.

Setting And Participants: Community-dwelling participants of the UK Biobank study aged 65 and older (n = 32,619) in the United Kingdom.

Impact of mobile phone use on accidental falls risk in young adult pedestrians.

Background: Mobile phone use is known to be a distraction to pedestrians, increasing their likelihood of crossing into oncoming traffic or colliding with other people. However, the effect of using a mobile phone to text while walking on gait stability and accidental falls in young adults remains inconclusive. This study uses a 70 cm low friction slip hazard and the threat of hazard to investigate the effects of texting while walking on gait stability, the ability to recover balance after a slip hazard and accidental falls.

Prediction of Incident Depression in Middle-Aged and Older Adults using Digital Gait Biomarkers Extracted from Large-Scale Wrist Sensor Data.

Objectives: To determine if digital gait biomarkers captured by a wrist-worn device can predict the incidence of depressive episodes in middle-age and older people.

Design: Longitudinal cohort study.

Setting And Participants: A total of 72,359 participants recruited in the United Kingdom.

Development and large-scale validation of the Watch Walk wrist-worn digital gait biomarkers.

Digital gait biomarkers (including walking speed) indicate functional decline and predict hospitalization and mortality. However, waist or lower-limb devices often used are not designed for continuous life-long use. While wrist devices are ubiquitous and many large research repositories include wrist-sensor data, widely accepted and validated digital gait biomarkers derived from wrist-worn accelerometers are not available yet.

Short Daily-Life Walking Bouts and Poor Self-Reported Health Predict the Onset of Depression in Community-Dwelling Older People: A 2-Year Longitudinal Cohort Study.

Objectives: This study aimed to assess whether the amount and quality of daily-life walking obtained using wearable technology can predict depression onset over a 2-year period, independently of self-reported health status.

Design: Longitudinal cohort study.

Setting And Participants: Three-hundred twenty-two community-dwelling older people recruited in Sydney, Australia.

Adaptation and validation of the Chinese version of Dyspnoea-12 scale in individuals with chronic obstructive pulmonary disease.

Introduction: Dyspnoea-12 scale is a validated assessment tool, capturing the perception of dyspnoea and its physical and affective effects in individuals with chronic obstructive pulmonary disease (COPD). A validated version for the Chinese-speaking population has been unavailable.

Objective: To develop a Chinese version of D-12 (D-12-C) scale and evaluate its validity and reliability.

Prevalence/Incidence of Low Back Pain and Associated Risk Factors Among Nursing and Medical Students: A Systematic Review and Meta-Analysis.

Objective: To summarize evidence regarding the prevalence and incidence of low back pain and associated risk factors in nursing and medical students. TYPE: Systematic review and meta-analysis.

Literature Survey: The protocol was registered with PROSPERO (CRD42015029729).

Associations between sport participation and knee symptoms: a cross-sectional study involving 3053 undergraduate students.

Background: While a number of studies have investigated knee symptoms among elite athletes, few have directly compared the association between engagement in different sports and knee symptoms among young adults in the general population. The current study aimed to investigate the relation between sports participation hours, type/ number of sports engaged, self-rated competitiveness and knee symptoms among undergraduates.

Methods: Undergraduates were invited to participate in a self-administered online survey through invitation emails.