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. METHODS: Participants were assessed at baseline on daily-life walking speed, quality, quantity and distribution using wrist-worn accelerometers for up to 7 days. Univariable and multivariable Cox proportional hazard regression models were used to analyse the associations between these parameters and injurious falls for up to 9 years. RESULTS: Five percent of the participants (n = 1,627) experienced at least one fall requiring medical attention over a mean of 7.0 ± 1.1 years. Daily-life walking speed, gait quality, quantity of walking and distribution of daily walking were all significantly associated with the incidence of injurious falls (P < 0.05). After adjusting for sociodemographics, lifestyle factors, comorbidities, handgrip strength and reaction time; running duration, total step counts and usual walking speed were identified as independent and significant predictors of falls (P < 0.01). These associations were consistent in those without a history of previous fall injuries. In contrast, step regularity was the only risk factor for those with a previous fall history after adjusting for covariates. CONCLUSIONS: Daily-life gait speed, quantity and quality, derived from wrist-worn sensors, are significant predictors of injurious falls in older people. These digital gait biomarkers could potentially be used to identify fall risk in screening programs and integrated into fall prevention strategies.

Preliminary evidence for physical activity following pelvic exenteration: a pilot longitudinal cohort study.

BACKGROUND: The physical activity (PA) level of patients undergoing major cancer surgery remains unclear. This pilot study aimed to: (i) Compare preoperative PA level between patients undergoing major cancer surgery and the general population; (ii) describe PA trajectories following major cancer surgery; (iii) Compare objective versus subjective PA measures in patients undergoing major cancer surgery; and (iv) Investigate the association between preoperative PA level and postoperative outcomes. METHODS: Patients undergoing pelvic exenteration between September/2016 and September/2017 were included and followed at preoperative, 6-weeks and 6-months postoperative. PA was measured using the International Physical Activity Questionnaire Short-Form and McRoberts activity monitor. Analyses were performed using SPSS. RESULTS: This pilot study included 16 patients. When compared to the general population, patients undergoing major cancer surgery presented a reduced preoperative PA level. PA levels decreased at 6 weeks but returned to preoperative levels at 6 months postoperative. Objective and subjective measures of PA were comparable, with some variables presenting strong correlations. A higher preoperative level PA was associated with an absence of postoperative complications and better quality of life outcomes. CONCLUSIONS: Patients undergoing major cancer surgery demonstrated lower PA levels when compared to the general population. PA trajectories decreased at 6 weeks postoperative, returning to preoperative levels within 6-months. In this cohort, it seems that higher preoperative PA level may improve postoperative surgical outcomes; however, this preliminary evidence should be confirmed in a larger cohort.

Advances in Remote Respiratory Assessments for People with Chronic Obstructive Pulmonary Disease: A Systematic Review.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality. Advances in remote technologies and telemedicine provide new ways to monitor respiratory function and improve chronic disease management. However, telemedicine does not always include remote respiratory assessments, and the current state of knowledge for people with COPD has not been evaluated. OBJECTIVE: Systematically review the use of remote respiratory assessments in people with COPD, including the following questions: What devices have been used? Can acute exacerbations of chronic obstructive pulmonary disease (AECOPD) be predicted by using remote devices? Do remote respiratory assessments improve health-related outcomes? MATERIALS AND METHODS: The review protocol was registered (PROSPERO 2016:CRD42016049333). MEDLINE, EMBASE, and COMPENDEX databases were searched for studies that included remote respiratory assessments in people with COPD. A narrative synthesis was then conducted by two reviewers according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RESULTS: Fifteen studies met the inclusion criteria. Forced expiratory volume assessed daily by using a spirometer was the most common modality. Other measurements included resting respiratory rate, respiratory sounds, and end-tidal carbon dioxide level. Remote assessments had high user satisfaction. Benefits included early detection of AECOPD, improved health-related outcomes, and the ability to replace hospital care with a virtual ward. CONCLUSION: Remote respiratory assessments are feasible and when combined with sufficient organizational backup can improve health-related outcomes in some but not all cohorts. Future research should focus on the early detection, intervention, and rehabilitation for AECOPD in high-risk people who have limited access to best care and investigate continuous as well as intermittent monitoring.

Good lateral harmonic stability combined with adequate gait speed is required for low fall risk in older people.

BACKGROUND: Good lateral harmonic stability in gait may be important for minimising fall risk in older people because many falls occur during walking when the base of support is narrowest in the mediolateral (ML) direction. However, the traditional ML harmonic ratio (MLHR) may be a sub-optimal measure of gait quality because of insufficient frequency resolution. OBJECTIVE: The primary objective was to investigate if a new measure of lateral harmonic stability, the 8-step MLHR, could discriminate older fallers from non-fallers while taking different walking speeds into account. METHODS: Repeat walks over 20 m were completed by 96 older people (mean age 80, SD 4 years); 35 participants had a history of one or more falls in the past year. The traditional MLHR and the 8-step MLHR were obtained from an accelerometer attached to the sacrum. RESULTS: Compared to the traditional MLHR, the 8-step MLHR demonstrated similar univariate ability to identify significant differences in fall risk based on age, walking speed and physiology (p ≤ 0.05). When differences in walking speed were taken into account, we observed that participants who walked both faster than average and had above-average lateral harmonic stability (by the 8-step MLHR) were 5.3 times less likely to be fallers than all other participants (relative risk: 0.19, 95% confidence interval: 0.06-0.57). For the traditional MLHR, however, no significant differences between the fallers and non-fallers were evident. CONCLUSIONS: The findings indicate that good lateral harmonic stability interacts with adequate gait speed and, when coincident, are associated with reduced fall risk in older people. Future research could examine whether interventions focusing on enhancing both gait speed and lateral stability can reduce fall risk and whether these combined gait measures can remotely predict deteriorating health using wearable technology.

Kinect-Based Five-Times-Sit-to-Stand Test for Clinical and In-Home Assessment of Fall Risk in Older People.

BACKGROUND: Accidental falls remain an important problem in older people. The five-times-sit-to-stand (5STS) test is commonly used as a functional test to assess fall risk. Recent advances in sensor technologies hold great promise for more objective and accurate assessments. OBJECTIVE: The aims of this study were: (1) to examine the feasibility of a low-cost and portable Kinect-based 5STS test to discriminate between fallers and nonfallers and (2) to investigate whether this test can be used for supervised clinical, supervised and unsupervised in-home fall risk assessments. METHODS: A total of 94 community-dwelling older adults were assessed by the Kinect-based 5STS test in the laboratory and 20 participants were tested in their own homes. An algorithm was developed to automatically calculate timing- and speed-related measurements from the Kinect-based sensor data to discriminate between fallers and nonfallers. The associations of these measurements with standard clinical fall risk tests and the results of supervised and unsupervised in-home assessments were examined. RESULTS: Fallers were significantly slower than nonfallers on Kinect-based measures. The mean velocity of the sit-to-stand transitions discriminated well between the fallers and nonfallers based on 12-month retrospective fall data. The Kinect-based measures collected in the laboratory correlated strongly with those collected in the supervised (r = 0.704-0.832) and unsupervised (r = 0.775-0.931) in-home assessments. CONCLUSION: In summary, we found that the Kinect-based 5STS test discriminated well between the fallers and nonfallers and was feasible to administer in clinical and supervised in-home settings. This test may be useful in clinical settings for identifying high-risk fallers for further intervention or for regular in-home assessments in the future.

Age-associated changes in head jerk while walking reveal altered dynamic stability in older people.

Many older people have impaired dynamic stability, and up to one in three people over 65 fall each year. It is thought that older people walk more slowly to compensate for reduced capabilities. Here, we investigate whether head jerk, the first time derivative of acceleration, can further our understanding of age-associated changes in dynamic stability while walking. Gait parameters including cadence, step length, walking speed, harmonic ratios, step time variability, and jerk were measured in 43 young and 100 older people using accelerometers securely attached to the head and pelvis. Older people presented significantly (p ≤ 0.004) more mediolateral (ML) head jerk, but significantly less vertical (VT) head jerk. The dimensionless ratio, ML/VT jerk, demonstrated superior ability (89 % accuracy) in differentiating older from younger people. Principal component analysis indicated that ML/VT jerk was a distinct gait construct. ML/VT jerk was highly reliable, normally distributed, independent of stature or gender, and relatively unaffected by walking speed. In older people, reduced VT head jerk may indicate reduced gait vigour, and increased ML head jerk may indicate age-associated changes to dynamic stability. The smoother head movements evident in our younger group may be because they were more able to rely on automatic control and the dynamic (pendulum-like) stability of their systems.

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

OBJECTIVE: Freezing of Gait (FOG) often described as the sensation of "the feet being glued to the ground" is prevalent in people with Parkinson's disease (PD) and severely disturbs mobility. In addition to tracking disease progression, precise detection of the exact boundaries for each FOG episode may enable new technologies capable of "breaking" FOG in real time. This study investigates the limits of sensitivity and performance for automatic device-based FOG detection. METHODS: Eight machine-learning classifiers (including Neural Networks, Ensemble & Support Vector Machine) were developed using (i) accelerometer and (ii) accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed a walking and mobility task designed to elicit FOG. Two clinicians independently annotated the precise FOG episodes using synchronized video according to international guidelines, which were incorporated into a flowchart algorithm developed for this study. Device-detected FOG episodes were compared to the annotated FOG episodes using 10-fold cross-validation to determine accuracy and with Interclass Correlation Coefficients (ICC) to assess level of agreement. RESULTS: Development used 50,962 windows of data representing over 10 hours of data and annotated activities. Very strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity and ICC1,1  =  0.97 for total FOG duration). Device-based performance varied by method, complexity and cost matrix. The Neural Network that used only 67 accelerometer features provided a good balance between high sensitivity to FOG (89% sensitivity, 81% specificity and ICC1,1  =  0.83) and solution stability (validation loss ≤ 5%). CONCLUSION: The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The superior agreement between clinicians indicates there is room to improve future device-based FOG detection by using larger and more varied data sets. SIGNIFICANCE: This study has clinical implications with regard to improving PD care by reducing reliance on clinical FOG assessments and time-consuming visual inspection. It shows high sensitivity to automatically detect FOG is possible.

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. Group-based trajectory analysis was used to identify patterns of depressive symptom development over 6 years of follow-up. Strengths of associations between baseline functional test performances and depressive symptom trajectories were evaluated with univariable ordinal models. Subsequently, the adjusted cumulative odds ratio for the association between identified risk factors, demographic factors and baseline anti-depressant use were measured using multivariable ordinal logistic regression. RESULTS: Three distinct depressive symptom trajectories were identified: a low-and-stable course (10% of participants), a low-and-increasing course (81%) and a moderate-and-increasing course (9%). Timed Up and Go test time was the strongest risk factor of depressive symptom trajectory, followed by Five Times Sit-to-Stand test performance, planned physical activity levels, and knee extension strength (adjusted standardised ORs 1.65, 95% CI 1.34-2.04; 1.44, 95% CI 1.16-1.77; 1.44, 95% CI 1.17-1.76 and 1.41, 95% CI 1.15-1.73 respectively). After adjusting for age, sex, body mass index and baseline anti-depressant use, Timed Up and Go test performance and knee extension strength were independently and significantly associated with depressive trajectories. CONCLUSIONS: Timed Up and Go test times, Five Times Sit-to-Stand test performance, planned physical activity levels and knee extension strength are associated with three discrete depressive symptom trajectories. These clinical tests may help identify older adults aged 70-90 years at risk of developing depressive symptoms and help guide subsequent strength and mobility interventions.

Orthotic shorts for improving gait and walking in multiple sclerosis: a feasibility study.

PURPOSE: To explore the acceptability and potential efficacy of orthotic shorts in people with multiple sclerosis. MATERIALS AND METHODS: This mixed-methods, cross-over study utilised qualitative data to investigate acceptability, including perceived effectiveness. Quantitative data included wear times, self-selected walking speed, spatiotemporal gait parameters, and participant-perceived walking ability. Fifteen participants were assessed with and without two pairs of custom-made shorts: one designed as an orthotic and a second looser pair. Each were worn at home for two weeks. Semi-structured interviews were conducted at the first and final appointments. Quantitative data were analysed using Cohen's d; qualitative analysis used a thematic framework. A triangulation protocol integrated qualitative and quantitative data. RESULTS: Orthotic shorts were acceptable to most users who described improved control, stability, and function. Where shorts were less acceptable, this was due to restriction of hip flexion or appearance. Effect sizes were in the moderate category for participant-perceived walking ability and for those spatiotemporal gait parameters that reflect mediolateral stability. Small effect sizes were seen for walking speed and related spatiotemporal parameters, such as step length. CONCLUSION: Orthotic shorts are acceptable and potentially efficacious for improving walking, stability, and function in people with multiple sclerosis. Further research and design development are warranted.Implications for rehabilitationOrthotic shorts are a type of fabric orthosis that have not been previously researched but might assist pelvic stability.Orthotic shorts appear to be acceptable to those people with multiple sclerosis who perceive themselves to be unstable around the trunk and hips.Orthotic shorts might improve gait stability and self-perceived walking ability.

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. METHODS: Participants were assessed at baseline on gait quantity, speed, intensity, quality, walk length distribution, and walk-related arm movement proportions using wrist-worn accelerometers for up to 7 days. Univariable and multivariable Cox proportional-hazard regression models were used to analyze the associations between these parameters and diagnosed incident depressive episodes for up to 9 years. RESULTS: A total of 1332 participants (1.8%) had incident depressive episodes over a mean of 7.4 ± 1.1 years. All gait variables, except some walk-related arm movement proportions, were significantly associated with the incidence of depressive episodes (P < .05). After adjusting for sociodemographic, lifestyle, and comorbidity covariates; daily running duration, steps per day, and step regularity were identified as independent and significant predictors (P < .001). These associations held consistent in subgroup analysis of older people and individuals with serious medical conditions. CONCLUSIONS AND IMPLICATIONS: The study findings indicate digital gait quality and quantity biomarkers derived from wrist-worn sensors are important predictors of incident depression in middle-aged and older people. These gait biomarkers may facilitate screening programs for at-risk individuals and the early implementation of preventive measures.

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. First, algorithms were developed and tested using data from 101 participants aged 19 to 91 (47 ± 18) years. Participants wore an AX3 accelerometer (Axivity, UK) on their dominant wrist while undertaking daily life activities with electronic walkway data used for ground truth. Subsequently, prediction models for dementia, depression and death were developed using the data of 47,406 participants (≥ 60 years) from the UK Biobank study. Daily walking speeds were derived from 7-day AX3 data with time-to-events using electronic health records. The accuracy of derived walking speeds was assessed using root mean square error (RMSE). Time-to-events were modelled using Cox regression with inverse hazard ratios reported for univariable models and Harrell's concordance for multivariable models. Derived walking speeds had an RMSE of between 3% and 4% depending on arm position. We found that for simple models, maximal walking speed was significantly better than usual walking speed at predicting time to dementia (1.62 vs 1.34), depression (1.29 vs 1.17) and death (1.56 vs 1.27). However, the addition of known risk factors in subsequent multivariable models reduced the apparent benefit of using maximal as opposed to usual daily walking speed as the gait parameter. In summary, walking speed was accurately measured with a wrist-worn device, and maximal daily waking speed may be better than usual daily walking speed at predicting some adverse health outcomes.Clinical Relevance- This study demonstrated the validity of using a simple and unobtrusive wrist-worn sensor to remotely assess daily walking speed. As a single, modifiable and easily understood measure, maximal walking speed was shown to be better than usual walking speed at predicting time-to-dementia, depression and death. Therefore, the inclusion of maximal daily walking speed into screening programs and clinical interventions presents a promising area for further research.

The effects of optic flow on postural stability: Influence of age and fall risk.

BACKGROUND: Optic flow provides dynamic information relating to body position and motion with respect to visual frames of reference. This study investigated the effects of optic flow stimuli presented in four directions on postural stability in young and older adults. METHODS: Twenty-five young (20-40 years) and 51 older (≥65 years) people participated in this study, with the older group classified into low fall risk (n = 27), and high fall risk (n = 24) sub-groups. While standing in a dark room, participants viewed static scattered white dots for 30 s, followed by 30 s periods of optic flow consisting of white dots "moving" in one of four flow directions, randomised: radial expansion and contraction, circular anti-clockwise and clockwise. Centre of pressure (CoP) position, postural sway in anteroposterior (AP) and mediolateral (ML) axes, and muscle activity of tibialis anterior (TA), gastrocnemius medialis (GM) and tensor fascia latae (TFL) were recorded. RESULTS: Across groups, the four optic flow stimuli induced increased AP sway and three of the four optic flow stimuli induced increased ML sway, with concomitant increases in muscle activity, indicating optic flow stimuli induced a generalised destabilising, rather than a direction-specific, effect. Only one optic flow condition (radial contraction) induced a change in average CoP position, and this may reflect the adoption of a protective stance position to avoid a backward fall. Optic flow destabilised postural control more in older people compared with younger people, and radial expansion stimuli destabilised ML postural control more in the older high fall risk group compared with the older low fall risk group. CONCLUSION: Optic flow stimuli have a generalised destabilising effect on postural control across groups as shown by non-directional specific increases in postural sway and muscular activity. Optic flow stimuli have a greater impact on postural stability in older compared with younger adults and this is more pronounced in the ML plane for older people at increased risk of falls.

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. Methods: Fifty healthy young adults performed six walking tasks, and one seated texting task in random order. The walks were conducted over a 10-m walkway. Four progressive hazard levels were used: 1) Seated; 2) Normal Walk (walking across the walkway with no threat of a slip); 3) Threat (walking with the threat of a slip); and 4) Slip (walking with an actual 70 cm slip hazard). The three walking conditions were repeated twice with and without the mobile phone texting dual-task. Gait kinematics and trunk posture were recorded using wearable sensors attached to the head, trunk, pelvis and feet. Study outcomes were analyzed using repeated measures analysis of variance with significance set to P≤.05. Results: Mobile phone use significantly impaired postural balance recovery when slipping, as demonstrated by increased trunk sway. Mobile phone use negatively impacted gait stability as demonstrated by increased step time variability and decreased harmonic ratios. Increased hazard levels also led to reduced texting accuracy. Conclusions: Using a mobile phone to text while walking may compete with locomotor tasks, threat assessment and postural balance control mechanisms, which leads to an increased risk of accidental falls in young adults. Pedestrians should therefore be discouraged through new educational and technology-based initiatives (for example a "texting lock" on detection of walking) from texting while walking on roadside footpaths and other environments where substantial hazards to safety exist.

Combined Reactive and Volitional Step Training Improves Balance Recovery and Stepping Reaction Time in People With Parkinson's Disease: A Randomised Controlled Trial.

BACKGROUND: Falls are frequent and devastating events for people with Parkinson's disease (PD). Here, we investigated whether laboratory-based reactive step training combined with home-based volitional step training was effective in improving balance recovery and stepping ability in people with PD. METHODS: Forty-four people with idiopathic PD were randomized into intervention or control groups. Intervention participants performed unsupervised volitional step training using home-based exergames (80+ minutes/week) for 12 weeks and attended reactive step training sessions in which they were exposed to slip and trip perturbations at 4 and 8 weeks. Control participants continued their usual activities. Primary outcomes were balance recovery following an induced-trip/slip and choice stepping reaction time (CSRT) at the 12-week reassessment. Secondary outcomes comprised sensorimotor, balance, cognitive, psychological, complex stepping (inhibitory CSRT and Stroop Stepping Test [SST]), gait measures, and falls experienced in everyday life. RESULTS: At reassessment, the intervention group had significantly fewer total laboratory-induced falls and faster CSRT compared to the control group (P < .05). The intervention group also had significantly faster inhibitory CSRT and SST movement times and made fewer mistakes in the SST (P < .05). There were no significant differences in the rate of every day falls or other secondary outcome measures between the groups. CONCLUSION: Combined volitional and reactive step training improved balance recovery from an induced-perturbation, voluntary stepping time, and stepping accuracy in cognitively challenging tests in people with PD. Further research is required to determine whether such combined step training can prevent daily-life falls in this population.

Immediate Effects of Lower Limb Sensory Simulation Using Smart Socks to Stabilize Gait in People with Parkinson's Disease.

People with Parkinson's disease (PD) experience gait impairment that can lead to falls and poor quality of life. Here we investigate the feasibility of using smart socks to stimulate the lower limbs of people with PD to reduce excessive step time variability during walking. We hypothesised that rythmic excitation of lower limb afferents, matched to a participant's comfortable pace, would entrain deficient neuro-muscular signals resulting in improved gait. Five people with mild to moderate PD symptoms (70 ± 9 years) were tested on medication before and after a 30-minute familierization session. Paired t-tests and Cohen's d were used to assess gait changes and report effect sizes. Participant experiences were recorded through structured interviews. Lower limb stimulation resulted in an acute 15% increase in gait speed (p=0.006, d=0.62), an 11% increase in step length (p=0.04, d=0.35), a 44% reduction in step time variability (p=0.03, d=0.91), a 22% increase in perceived gait quality (p=0.04, d=1.17), a 24% reduction in mental effort to walk (p=0.02, d=0.79) and no statistical difference for cadence (p=0.16). Participants commented positively on the benefit of stimulation during training but found that stimulation could be distracting when not walking and the socks hard to put on. While the large effects for step time variability and percieved gait quality (Cohen's d > 0.8) are promising, limitations regarding sample size, potential placebo effects and translation to the home environment should be addressed by future studies.Clinical Relevance- This study demonstrates the feasibility of using smart stimulating socks to reduce excessive step time variability in people with PD. As step time variability is a risk factor for falls, the use of smart textiles to augment future rehabilitation programs warrants further investigation.

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. METHODS: Participants were assessed at baseline on (1) depressive symptoms using the Patient Health Questionnaire-9; (2) average weekly physical activity levels over the past month using the Incidental and Planned Activity Questionnaire, (3) clinical mobility tests (ie, short physical performance battery, timed up-and-go test, 6-m walk test); and (4) amount and quality of daily-life walking assessed with a trunk accelerometer (MoveMonitor, McRoberts) for 1 week. Participants were followed up for onset of depressive symptoms for 2 years at 6-monthly intervals. RESULTS: Daily-life walking (ie, gait intensity in the mediolateral axis, daily step counts, duration of longest walk) and self-rated health predicted the new onset of depressive symptoms at 2 years in univariable logistic regression models. In multivariable models containing a self-rated health measure, clinical mobility tests were not predictive of the onset of depressive symptoms. In contrast, a measure of daily-life walking (duration of longest walking bout) was identified as a significant predictor of depressive symptom onset [standardized odds ratio (SOR) 2.44, 95% CI 1.62-3.76] independent of self-rated health (SOR 1.51, 95% CI 1.16-1.96), with these 2 measures achieving a satisfactory prediction accuracy (area under the curve = 0.67, sensitivity: 0.78, specificity: 0.52). CONCLUSIONS AND IMPLICATIONS: A risk algorithm based on daily-life walking bouts and self-reported health demonstrated good accuracy for the prediction of depression onset in older people over 2 years. Wearable sensor data compared favorably with clinical mobility screens and may add important independent information for screening for depression among older people.

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. Here we describe the development of advanced signal processing algorithms that extract digital gait biomarkers from wrist-worn devices and validation using 1-week data from 78,822 UK Biobank participants. Our gait biomarkers demonstrate good test-retest-reliability, strong agreement with electronic walkway measurements of gait speed and self-reported pace and significantly discriminate individuals with poor self-reported health. With the almost universal uptake of smart-watches, our algorithms offer a new approach to remotely monitor life-long population level walking speed, quality, quantity and distribution, evaluate disease progression, predict risk of adverse events and provide digital gait endpoints for clinical trials.

Pain, balance, and mobility in people 1 year after total knee arthroplasty: a non-randomized cross-sectional pilot study contrasting posterior-stabilized and medial-pivot designs.

BACKGROUND: Total knee arthroplasty (TKA) is a common treatment for severe knee osteoarthritis. Medial-pivot TKA systems (MP-TKA) are theoretically better than posterior-stabilized TKA systems (PS-TKA) in improving static and dynamic balance of patients although it is difficult to objectively quantify these balance parameters in a clinical setting. Therefore, this pilot study aimed to evaluate the feasibility of using wearable devices in a clinical setting to examine whether people with MP-TKA have better postoperative outcomes than PS-TKA, and their balance control is more akin to age-matched asymptomatic controls. METHODS: The current cross-sectional pilot study recruited 57 participants with 2 different prosthesis designs (20 PS-TKA, 18 MP-TKA) and 19 asymptomatic controls. At 1-year post-TKA, pain, knee stiffness, and physical function were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Static balance, mobility, and gait stability of the participants were evaluated based on data collected from wearable motion sensors during the near tandem stance, timed-up-and-go, and 6-min walk tests. RESULTS: Compared to asymptomatic controls, both TKA groups reported significantly more pain and stiffness and demonstrated reduced functional mobility, increased stride-time-variability, and impaired balance. After Bonferroni adjustment, no significant differences in pain, balance, and mobility performance were observed between PS-TKA and MP-TKA participants 1 year after surgery. However, there was a trend for increased anteroposterior sway of the lumbar and head regions in the MP-TKA participants when undertaking the near tandem stance test. The wearable motion sensors were easy to use without any adverse effects. CONCLUSIONS: It is feasible to use wearable motion sensors in a clinical setting to compare balance and mobility performance of patients with different TKA prothesis designs. Since this was a pilot study and no definite conclusions could be drawn, future clinical trials should determine the impacts of different TKA prosthesis designs on post-operative outcomes over a longer follow-up period.

Quantifying upper-limb motor impairment in people with multiple sclerosis: A physiological profiling approach.

BACKGROUND: . Upper-limb sensory and motor impairments are common in people with multiple sclerosis (MS), yet the current gold standard criteria for documenting functional impairment largely focuses on mobility, balance and postural stability. OBJECTIVE: . We aimed to determine the validity of the upper-limb Physiological Profile Assessment (PPA) in people with MS by investigating whether the included domains of muscle strength, dexterity, arm stability, position sense, skin sensation and bimanual coordination 1) are sensitive in differentiating people with MS from healthy controls and 2) correlate with a validated measure of upper-limb function and a scale for quantifying disability in MS. METHODS: . In a cross-sectional study, 40 participants with MS and 80 healthy controls completed all 13 of the upper-limb PPA tests within a single session. RESULTS: . People with MS were impaired across all physiological domains tested. Performance in 4 of the 13 tests was correlated with a validated measure of self-reported upper-limb function (Pearson's r or Spearman's rho -0.333-0.441), whereas 3 tests were associated with the degree of MS-specific disability (Spearman's rho -0.318; 0.456). CONCLUSIONS: . The upper-limb PPA offers a valid and clinically suitable assessment of upper-limb function in people with MS. Clinicians should prioritize assessments of motor speed, fine motor control and functional tasks in their assessment of upper-limb function in people with MS because these domains are the most commonly and significantly impaired.

Quantifying upper limb motor impairment in chronic stroke: a physiological profiling approach.

Upper limb motor impairments, such as muscle weakness, loss of dexterous movement, and reduced sensation, are common after a stroke. The extent and severity of these impairments differ among individuals, depending on the anatomical location and size of lesions. Identifying impairments specific to the individual is critical to optimize their functional recovery. The upper limb Physiological Profile Assessment (PPA) provides quantitative measures of key physiological domains required for adequate function in the upper limbs. The present study investigates the use of the upper limb PPA in a chronic stroke population. Fifty participants with chronic stroke completed all tests of the upper limb PPA with both their affected and less affected upper limbs. Performance in each test was compared to that of 50 age- and sex-matched control subjects with no history of a stroke. Correlations between test performance and validated measures of stroke, sensorimotor function, and disability were examined. Compared with control subjects, people with stroke demonstrated substantially impaired upper limb PPA performance for both their affected and less affected limbs. Performance in the upper limb PPA was associated with validated measures of sensorimotor function specific to the stroke population (Fugl-Meyer Assessment) and stroke-related disability (Stroke Impact Scale). The upper limb PPA shows good concurrent validity as a means to quantify upper limb function in a chronic stroke population. These tests identify domain-specific deficits and could be further tailored to an individual patient by the clinician to inform rehabilitation and track recovery.NEW & NOTEWORTHY Upper limb motor impairment is a common manifestation after stroke, compromising independence in fundamental daily activities involving the ability to reach, grasp, and manipulate objects. The upper limb Physiological Profile Assessment (PPA) offers a means of quantifying performance of the individual sensorimotor domains that are essential for upper limb function. Establishing individual performance profiles based on age- and sex-based normative scores may facilitate individualized treatment decisions by identifying the stroke patient's specific strengths and limitations.