Gait Measures Research Articles

Self-reported physical activity and gait in older adults without dementia: A longitudinal study.

Physical activity (PA) is associated with higher gait speed. We aimed to examine the associations between PA and change in spatial and temporal gait measures as well as fall risk in community-dwelling individuals free of dementia. Longitudinal study among 4173 individuals aged ≥50 years (mean age 71 years; 2078 males; median follow-up 4 years) enrolled in the Mayo Clinic Study of Aging. Self-reported late-life PA was used to calculate overall PA and moderate-vigorous PA (MVPA) scores. Gait was assessed using GAITRite® and Zeno™ systems. Incident falls information was based on diagnostic codes retrieved from medical records. We ran linear mixed effects models to examine associations between z-scored PA variables and longitudinal gait parameters, adjusted for age, sex, education, body mass index (BMI), medical comorbidities, and including interactions between PA and time since baseline. In secondary analyses, we calculated Cox Proportional hazard models with age as time scale predicting incident falls by PA, adjusting for sex, education, BMI, medical comorbidities, and falls history. At baseline, higher PA was associated with higher velocity (overall PA: estimate 2.9935; MVPA: 2.2961; p < 0.001), higher cadence (overall PA: 1.0665; MVPA: 0.9073; p < 0.001), greater stride length (overall PA: 2.0805; MVPA: 1.4726; p < 0.001), shorter double support time (overall PA: -0.0257; MVPA: -0.0205; p < 0.001), and lower stance time variability (overall PA: -0.0204, p < 0.001; MVPA: -0.0152; p = 0.006). Overall PA was longitudinally associated with less decline in cadence, and MVPA with less increase in intraindividual stance time variability. Overall PA (Hazard ratio 0.892, 95% confidence interval 0.828-0.961, p = 0.003) and MVPA (HR 0.901; 95% CI 0.835-0.973, p = 0.008) were associated with a decreased risk of incident falls. Late-life PA was associated with favorable gait outcomes and decreased risk of incident falls. Thus, late-life PA may help to maintain gait performance and decrease fall risk in old age.

Validity and reliability of running gait measurement with the ViMove2 system.

Running biomechanics have traditionally been analysed in laboratory settings, but this may not reflect natural running gait. Wearable technology has the potential to enable precise monitoring of running gait beyond the laboratory. This study aimed to evaluate the analytical validity and intra-session reliability of temporal running gait outcomes measured by the ViMove2 wearable system in healthy adults. Seventy-four healthy adults (43 males, 31 females, aged 18-55 years) wore the inertial device, ViMove2 on the tibia. Participants ran on a treadmill for one minute at various speeds (8, 10, 12, 14km/hr), completed in a standardised shoe (Saucony Guide Runner). Running gait was measured with the ViMove2 wearable and 3D motion capture (Vicon). Temporal running gait outcomes included ground contact time (GCT) and cadence (steps/min). GCT and cadence from the ViMove2 had face validity with expected changes in outcome with different running speeds, but ViMove2 tended to over-estimate GCT, and under-estimate cadence compared to the reference, especially at slower speeds. GCT demonstrated moderate to good agreement to the reference at speeds >10km/hr, but poor agreement at 8km/hr and within female runners. Cadence had moderate to excellent agreement across speeds compared to the reference. GCT and cadence had excellent reliability across speeds, but at 8km/hr GCT had good agreement between trials. Overall, temporal gait outcomes of GCT and cadence can be measured with the ViMove2, but accuracy and reliability are impacted at slow running speeds and within female runners. Future work is needed to clarify sex or speed-dependent corrections to algorithms / outcomes to aid interpretation and application.

Artificial intelligence-assisted oculo-gait measurements for cognitive impairment in cerebral small vessel disease.

Oculomotor and gait dysfunctions are closely associated with cognition. However, oculo-gait patterns and their correlation with cognition in cerebral small vessel disease (CSVD) remain unclear. Patients with CSVD from a hospital-based cohort (n = 194) and individuals with presumed early CSVD from a community-based cohort (n = 319) were included. Oculo-gait patterns were measured using the artificial intelligence (AI) -assisted 'EyeKnow' eye-tracking and 'ReadyGo' motor evaluation systems. Multivariable linear and logistic regression models were employed to investigate the association between the oculo-gait parameters and cognition. Anti-saccade accuracy, stride velocity, and swing velocity were significantly associated with cognition in both patients and community dwellers with CSVD, and could identify cognitive impairment in CSVD with moderate accuracy (area under the curve [AUC]: hospital cohort, 0.787; community cohort, 0.810) after adjusting for age and education. The evaluation of oculo-gait features (anti-saccade accuracy, stride velocity, and swing velocity) may help screen cognitive impairment in CSVD. Oculo-gait features (lower anti-saccade accuracy, stride velocity, and swing velocity) were associated with cognitive impairment in cerebral small vessel disease (CSVD). Logistic model integrating the oculo-gait features, age, and education level moderately distinguished cognitive status in CSVD. Artificial intelligence-assisted oculomotor and gait measurements provide quick and accurate evaluation in hospital and community settings.

Best task and best gait measure to identify de novo and moderate Parkinson's disease: a lesson learned from a machine learning point of view

Best task and best gait measure to identify de novo and moderate Parkinson's disease: a lesson learned from a machine learning point of view

Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson’s disease

Parkinson’s disease (PD) presents diverse symptoms and comorbidities, complicating its diagnosis and management. The primary objective of this cross-sectional, monocentric study was to assess digital gait sensor data’s utility for monitoring and diagnosis of motor and gait impairment in PD. As a secondary objective, for the more challenging tasks of detecting comorbidities, non-motor outcomes, and disease progression subgroups, we evaluated for the first time the integration of digital markers with metabolomics and clinical data. Using shoe-attached digital sensors, we collected gait measurements from 162 patients and 129 controls in a single visit. Machine learning models showed significant diagnostic power, with AUC scores of 83–92% for PD vs. control and up to 75% for motor severity classification. Integrating gait data with metabolomics and clinical data improved predictions for challenging-to-detect comorbidities such as hallucinations. Overall, this approach using digital biomarkers and multimodal data integration can assist in objective disease monitoring, diagnosis, and comorbidity detection.

Repeatability of gait of children with spastic cerebral palsy in different walking conditions

Three-dimensional gait analysis is the ‘gold standard’ for measurement and description of gait. Gait variability can arise from intrinsic and extrinsic factors and may vary between walking conditions. This study aimed to define the inter-trial and inter-session repeatability in gait analysis data of children with cerebral palsy (CP) who were walking in four conditions, namely barefoot or with ankle–foot orthosis (AFO), and overground or treadmill. Ten children with spastic CP (7♀; 9.9y ± 3.5y; GMFCS-level I-III) were included in this study. Overall, we found good to excellent intra-class correlation (ICC)-values and favourable standard error of measurement (SEM)-values for the inter-session Gait Profile Score (ICC = 0.85–0.98, SEM = 0.45–0.91°) and Gait Variable Scores (ICC = 0.85–0.99, SEM = 0.22–1.11°) for the lower-limb joints. Taking the total joint-range-of-motion into account, the knee joint showed the most repeatable motion (%SEM = 0.5–1.8 %), while ankle motions showed the lowest repeatability (%SEM = 0.8 %–3.0 %). For the continuous waveform data, only the ankle joint showed repeatability differences between walking conditions, namely, smaller SEM-values for the AFO-condition (mean inter-trial = 0.14°; mean inter-session = 1.121°) in comparison to the barefoot-condition (mean inter-trial = 0.55°; mean inter-session = 2.22°). For all the kinetic parameters, the treadmill conditions showed smaller SEM-values in comparison to the overground condition. In conclusion three-dimensional gait analysis was found to be reliable in all four walking conditions for children with CP. The resulting measurement errors can be used as a reference during clinical interpretations of gait analyses.Clinical trial registration number: Trial ID from an internationally recognized trial registry (ClinicalTrials.gov): NCT06355869

In-Clinic and Natural Gait Observations master protocol (I-CAN-GO) to validate gait using a lumbar accelerometer

Traditional measurements of gait are typically performed in clinical or laboratory settings where functional assessments are used to collect episodic data, which may not reflect naturalistic gait and activity patterns. The emergence of digital health technologies has enabled reliable and continuous representation of gait and activity in free-living environments. To provide further evidence for naturalistic gait characterization, we designed a master protocol to validate and evaluate the performance of a method for measuring gait derived from a single lumbar-worn accelerometer with respect to reference methods. This evaluation included distinguishing between participants’ self-perceived different gait speed levels, and effects of different floor surfaces such as carpet and tile on walking performance, and performance under different bouts, speed, and duration of walking during a wide range of simulated daily activities. Using data from 20 healthy adult participants, we found different self-paced walking speeds and floor surface effects can be accurately characterized. Furthermore, we showed accurate representation of gait and activity during simulated daily living activities and longer bouts of outside walking. Participants in general found that the devices were comfortable. These results extend our previous validation of the method to more naturalistic setting and increases confidence of implementation at-home.

Gait performance in older adults across the cognitive spectrum: Results from the GAIT cohort.

Gait performance can provide valuable insights into cognitive functioning in older adult and may be used to screen for cognitive impairment. However, the optimal test condition and spatiotemporal parameter for accuracy have not yet been determined. This study aims to determine the gait measure with the highest accuracy identifying cognitive decline. A total of 711 participants were recruited, including 332 cognitively healthy individuals, 264 with mild cognitive impairment (MCI), and 115 with dementia, with a mean age of 72 years (interquartile range 69-76), and 43% (n = 307) of women. The participants underwent gait assessment in three different conditions, including a single task and dual tasks of counting backward by ones and naming animals. Gait performance was deteriorated as cognitive impairment progressed. The gait test performed during naming animals condition was the most accurate in differentiating between cognitive groups. Specifically, the naming animals gait speed was more accurate in discriminating control participants from those with cognitive impairment (area under the curve [AUC] = 76.9% for MCI and 99.7% for people with dementia with control group as reference). The coefficient of stride length variability while naming animals was the most effective parameter in discriminating between MCI and dementia groups (AUC = 96.7%). The naming animals dual-task gait test can be a valuable assessment for screening cognitive impairment in older adults, regardless of their cognitive abilities. The test is useful in clinical settings for subjects with a range of cognitive profiles.

Pushing the limit to reach meaningful change: the impact of intensity-driven exercise on clinical outcomes for individuals with Parkinson’s disease. A single-subject design

Purpose Parkinson’s disease creates an inability to perform previous learned autonomic tasks, such as walking, which worsens with disease progression. Recommendations to incorporate exercise at moderate to high intensities for this population has been established but there is limited knowledge about its impact on clinical based outcomes. The purpose of this research is to investigate the effectiveness of a 6-week intensity-driven walking program on clinical-based outcomes in individuals with PD. Materials/Methods Five individuals with PD were recruited for this single-subject withdrawal design (A-B-A-B) study. 6-minute walk performance and other core neurological measures of gait were collected. Intervention phases incorporated a 30-minute individualized intensity-driven treadmill walking program practiced at 65% or more of ones maximum heart rate. Increased treadmill speed, incline, and resistance were manipulated to reach the target heart rate zone. Results 6-minute walk test within condition visual analysis demonstrated a therapeutic change during intervention phases and a countertherapeutic change during withdraw periods for all 5 individuals. An abrupt therapeutic effect was demonstrated for all individuals between conditions with the percent of nonoverlapping data ranging from 70-90%. Band method analysis revealed a range of 9-19 sessions two standard deviations above baseline mean performances for all individuals. Conclusion To achieve sufficient walking performance, gait practiced at higher intensity levels may provide the optimal solution as an adjunct to standard care for individuals with PD who want to improve their walking.

Amplify Gait to Improve Locomotor Engagement in Spinal Cord Injury (AGILE SCI) trial: study protocol for an assessor blinded randomized controlled trial

BackgroundAmong ambulatory people with incomplete spinal cord injury (iSCI), balance deficits are a primary factor limiting participation in walking activities. There is broad recognition that effective interventions are needed to enhance walking balance following iSCI. Interventions that amplify self-generated movements (e.g., error augmentation) can accelerate motor learning by intensifying sensorimotor feedback and facilitating exploration of motor control strategies. These features may be beneficial for retraining walking balance after iSCI. We have developed a cable-driven robot that creates a movement amplification environment during treadmill walking. The robot applies a continuous, laterally-directed, force to the pelvis that is proportional in magnitude to real-time lateral velocity. Our purpose is to investigate the effects of locomotor training in this movement amplification environment on walking balance. We hypothesize that for ambulatory people with iSCI, locomotor training in a movement amplification environment will be more effective for improving walking balance and participation in walking activities than locomotor training in a natural environment (no applied external forces).MethodsWe are conducting a two-arm parallel-assignment intervention. We will enroll 36 ambulatory participants with chronic iSCI. Participants will be randomized into either a control or experimental group. Each group will receive 20 locomotor training sessions. Training will be performed in either a traditional treadmill environment (control) or in a movement amplification environment (experimental). We will assess changes using measures that span the International Classification of Functioning, Disability and Health (ICF) framework including 1) clinical outcome measures of gait, balance, and quality of life, 2) biomechanical assessments of walking balance, and 3) participation in walking activities quantified by number of steps taken per day.DiscussionTraining walking balance in people with iSCI by amplifying the individual’s own movement during walking is a radical departure from current practice and may result in new strategies for addressing balance impairments. Knowledge gained from this study will expand our understanding of how people with iSCI improve walking balance and how an intervention targeting walking balance affects participation in walking activities. Successful outcomes could motivate development of clinically feasible tools to replicate the movement amplification environment within clinical settings.Trial registrationNCT04340063.

Vibrotactile Foot Device for Freezing of Gait in Parkinson's Disease: A Pilot Study.

Vibrotactile stimulation has been studied in its efficacy of reducing freezing of gait (FOG) in patients with Parkinson's disease (PD). However, the results are still controversial. We evaluated the efficacy of a newly developed vibrotactile foot device on freezing severity and gait measures in PD patients with FOG. To evaluate the efficacy of vibrotactile foot device on PD patients with FOG. Thirty-three PD patients with FOG were examined during their "off" medication state. The efficacy of the vibrotactile foot device was evaluated using a gait protocol comprising walking trials with vibrotactile stimulation "off" and "on." Walking trials were videotaped for the offline rating by two movement disorder specialists. The Opal inertial sensor unit (128 Hz; Mobility Lab; APDM Inc., Portland, OR, USA) was used for quantitative gait analysis. The results demonstrated 33.1% reduction in number of FOG episodes (P < 0.001) and 32.6% reduction of freezing episodes (P < 0.001). Quantitative gait analysis showed a significant increase in step length (P = 0.033). A moderate negative correlation was observed between the change of percent time frozen and age (r = -0.415, P = 0.016). 73% of participants reported minimal to substantial improvement in walking with this vibrating stimulation delivered by the vibrotactile foot device. The vibrotactile foot device is an efficient device that could significantly reduce freezing severity and provide gait regulation to patients with PD experiencing frequent freezing. It could potentially be used in the home environment for improving the quality of life.

Tandem gait step-width increases more rapidly in more severely affected people with Parkinson's disease

IntroductionTandem gait performance reportedly predicts fall risk in people with Parkinson's disease (PwPD) and help distinguish PwPD from atypical parkinsonism. In a cross-sectional study, we previously showed that tandem gait step-width widens with increasing Hoehn and Yahr (H&Y) staging scores. In this longitudinal study, we aimed to determine if progression in tandem gait deficits is dependent on disease severity in PwPD. MethodsParticipants underwent an instrumented tandem gait measurement every 6 months for at least 2 years. The mean and variability of 4 tandem gait parameters were calculated at each visit: step-width, step-length, step-time, and step-velocity. The change in these parameters over time for 3 H&Y groups (stage 1, 2 and 2.5+) compared to aging controls was determined using a random coefficients regression model. The annual percent change in tandem gait parameters was correlated with initial disease features using Kendall's τB. Results66 participants were analyzed (46 PD, 20 controls). Mean step-width increased over time in an H&Y stage-dependent manner, with H&Y 2 and H&Y 2.5+ experiencing increases of 6% and 10% per year (p = 0.001 and 0.024 respectively). Annual percent-change in step-width was correlated with initial motor Unified Parkinson's Disease Rating Scale (UPDRS) scores (Kendall's τB = 0.229), total UPDRS scores (τB = 0.249), H&Y scores (τB = 0.266) and inversely correlated with Montreal Cognitive Assessment (MoCA) scores (τB = −0.209; ps ≤ 0.019). ConclusionTandem gait step-width widens over time more rapidly in more severely affected PD patients. These results suggest that tandem gait should be routinely clinically evaluated and considered in the management of imbalance in PwPD.

Physical Functioning, Physical Activity, and Variability in Gait Performance during the Six-Minute Walk Test.

Instrumenting the six-minute walk test (6MWT) adds information about gait quality and insight into fall risk. Being physically active and preserving multi-directional stepping abilities are also important for fall risk reduction. This analysis investigated the relationship of gait quality during the 6MWT with physical functioning and physical activity. Twenty-one veterans (62.2 ± 6.4 years) completed the four square step test (FSST) multi-directional stepping assessment, a gait speed assessment, health questionnaires, and the accelerometer-instrumented 6MWT. An activity monitor worn at home captured free-living physical activity. Gait measures were not significantly different between minutes of the 6MWT. However, participants with greater increases in stride time (ρ = -0.594, p < 0.01) and stance time (ρ = -0.679, p < 0.01) during the 6MWT reported lower physical functioning. Neither physical activity nor sedentary time were related to 6MWT gait quality. Participants exploring a larger range in stride time variability (ρ = 0.614, p < 0.01) and stance time variability (ρ = 0.498, p < 0.05) during the 6MWT required more time to complete the FSST. Participants needing at least 15 s to complete the FSST meaningfully differed from those completing the FSST more quickly on all gait measures studied. Instrumenting the 6MWT helps detect ranges of gait performance and provides insight into functional limitations missed with uninstrumented administration. Established FSST cut points identify aging adults with poorer gait quality.

Implementation of a unilateral hip flexion exosuit to aid paretic limb advancement during inpatient gait retraining for individuals post-stroke: a feasibility study

BackgroundDuring inpatient rehabilitation, physical therapists (PTs) often need to manually advance patients’ limbs, adding physical burden to PTs and impacting gait retraining quality. Different electromechanical devices alleviate this burden by assisting a patient’s limb advancement and supporting their body weight. However, they are less ideal for neuromuscular engagement when patients no longer need body weight support but continue to require assistance with limb advancement as they recover. The objective of this study was to determine the feasibility of using a hip flexion exosuit to aid paretic limb advancement during inpatient rehabilitation post-stroke.MethodsFourteen individuals post-stroke received three to seven 1-hour walking sessions with the exosuit over one to two weeks in addition to standard care of inpatient rehabilitation. The exosuit assistance was either triggered by PTs or based on gait events detected by body-worn sensors. We evaluated clinical (distance, speed) and spatiotemporal (cadence, stride length, swing time symmetry) gait measures with and without exosuit assistance during 2-minute and 10-meter walk tests. Sessions were grouped by the assistance required from the PTs (limb advancement and balance support, balance support only, or none) without exosuit assistance.ResultsPTs successfully operated the exosuit in 97% of sessions, of which 70% assistance timing was PT-triggered to accommodate atypical gait. Exosuit assistance eliminated the need for manual limb advancement from PTs. In sessions with participants requiring limb advancement and balance support, the average distance and cadence during 2-minute walk test increased with exosuit assistance by 2.2 ± 3.1 m and 3.4 ± 1.9 steps/min, respectively (p < 0.017). In sessions with participants requiring balance support only, the average speed during 10-meter walk test increased with exosuit by 0.07 ± 0.12 m/s (p = 0.042). Clinical and spatiotemporal measures of independent ambulators were similar with and without exosuit (p > 0.339).ConclusionsWe incorporated a unilateral hip flexion exosuit into inpatient stroke rehabilitation in individuals with varying levels of impairments. The exosuit assistance removed the burden of manual limb advancement from the PTs and resulted in improved gait measures in some conditions. Future work will understand how to optimize controller and assistance profiles for this population.

Relationship between hip contact force during gait and patient-reported outcome measures 6 months after total hip arthroplasty

PurposeEvaluating the hip contact force (HCF) during gait is important for assessing treatment outcomes after total hip arthroplasty (THA). This study investigated the relationship between patient-reported outcome measures (PROMs) and HCF during gait after THA as well as gait biomechanical factors affecting HCF during gait in relation to PROMs. MethodsIn total, 29 female patients who underwent THA with a 6-month follow-up were included in this study. Musculoskeletal model analysis was performed to obtain the first and second peak values of the HCF during gait and the minimum value between both peaks. PROMs were evaluated using the Japanese Orthopaedic Association Hip Disease Evaluation Questionnaire (JHEQ). The relationship between JHEQ and selected HCFs and between the HCF and gait biomechanical factors was examined. ResultsThe second peak value of HCF was positively related to the total JHEQ, movement, and mental health scores (r ​= ​−0.551, 0.410, and 0.495, respectively). A positive relationship was found between the second peak value of the HCF and hip flexion–extension range of motion (r ​= ​0.518), maximum hip abduction moment (r ​= ​0.432), and maximum knee extension moment (r ​= ​0.417). A negative relationship was found between the second peak value of the HCF and the maximum knee abduction moment (r ​= ​−0.458). ConclusionsThe second peak value of HCF during gait after THA was related to PROMs. The second peak value was related to the hip flexion–extension range of motion, maximum hip abduction moment, and maximum knee extension and abduction moment.

1103 Gait Analysis Using Wearables and AI in Predicting Peripheral Arterial Disease: A Systematic Review

Abstract Introduction Peripheral arterial disease (PAD) affects over 230 million people globally. The trajectory of this disease process can culminate in major amputation. These patients demonstrate statistically significant changes in gait including changes in stride length, plantarflexion and other spatiotemporal parameters. Aim To determine if alterations in gait parameters can be detected and measured accurately by wearables and AI in PAD patients and if these measurements are predictive of PAD progression. Method A systematic review was performed in line with PRISMA guidelines. MEDLINE, Embase, Web of Science and Scopus were used for database searches. A combination of medical subject headings (MeSH) regarding ‘PAD’, ‘gait’, ‘kinetics’, ‘biomechanics’, ‘ambulation’, ‘artificial intelligence’, ‘sensors’ and ‘smartphone data’ were employed in the primary search string. Screening, full text reviews and data extraction was conducted by 2 reviewers using Covidence. Bias was assessed using the Newcastle-Ottawa scale. Results 4719 studies were identified. 3873 were screened after de-duplication. 5 studies were included in the final review. The main methods of gait measurements included smartphones (iPhone and Samsung Galaxy), wearable sensors and motion sensor technology. Gait initiation parameters were sensitive in detecting gait impairment. iPhone pedometer demonstrated accuracy measuring steps comparable to reference Actigraph but was inaccurate measuring distance. Machine learning models including Random Forest algorithms and extreme gradient boosting, detected PAD patients with 89% and 92% accuracy respectively. Conclusions Wearables and AI algorithms can detect gait changes and differentiate PAD from non-PAD gait. All studies showed detective capability, however none demonstrated predictability of PAD. Limitations include accuracy and validation of measurement methods.

Association of dual task gait performance with cognitive outcomes among older adults: Piloting an inexpensive, portable assessment platform

Motor assessment has emerged as complementary evidence for the detection of late life cognitive disorders. Clinicians lack inexpensive, accurate, and portable tools for this purpose. To fill this void, the current study piloted measures from the Mizzou Point-of-care Assessment System a multimodal sensor platform. We examined the ability of these motor function measures to distinguish neurocognitive status and assessed their associations with cognitive performance. Data came from 42 older adults, including 16 with mild cognitive impairment (MCI). Participants performed dual task gait, pairing walking with serial subtraction by sevens, along with aa neuropsychological test battery. T-tests revealed that individuals with MCI demonstrated slower stride times (d = .55) and shorter stride lengths (d = .98) compared to healthy older adults. Results from hierarchical regression showed that stride time and stride length predicted cognitive performance across several domains, after controlling for cognitive status and demographics. Cognitive status moderated this relationship for global cognition and attention, wherein gait measures were significantly related to these outcomes for the cognitively normal group, but not the MCI group. Evidence from the current study provided preliminary support that MPASS measures demonstrate expected associations with cognitive performance and can distinguish amongst those with and without cognitive impairment.

Wearable Robot Design Optimization Using Closed-Form Human-Robot Dynamic Interaction Model.

Wearable robots are emerging as a viable and effective solution for assisting and enabling people who suffer from balance and mobility disorders. Virtual prototyping is a powerful tool to design robots, preventing the costly iterative physical prototyping and testing. Design of wearable robots through modelling, however, often involves computationally expensive and error-prone multi-body simulations wrapped in an optimization framework to simulate human-robot-environment interactions. This paper proposes a framework to make the human-robot link segment system statically determinate, allowing for the closed-form inverse dynamics formulation of the link-segment model to be solved directly in order to simulate human-robot dynamic interactions. The paper also uses a technique developed by the authors to estimate the walking ground reactions from reference kinematic data, avoiding the need to measure them. The proposed framework is (a) computationally efficient and (b) transparent and easy to interpret, and (c) eliminates the need for optimization, detailed musculoskeletal modelling and measuring ground reaction forces for normal walking simulations. It is used to optimise the position of hip and ankle joints and the actuator torque-velocity requirements for a seven segments of a lower-limb wearable robot that is attached to the user at the shoes and pelvis. Gait measurements were carried out on six healthy subjects, and the data were used for design optimization and validation. The new technique promises to offer a significant advance in the way in which wearable robots can be designed.

Remotely monitored physical activity from older people with cardiac devices associates with physical functioning

IntroductionAccelerometer-derived physical activity (PA) from cardiac devices are available via remote monitoring platforms yet rarely reviewed in clinical practice. We aimed to investigate the association between PA and clinical measures of frailty and physical functioning.MethodsThe PATTErn study (A study of Physical Activity paTTerns and major health Events in older people with implantable cardiac devices) enrolled participants aged 60 + undergoing remote cardiac monitoring. Frailty was measured using the Fried criteria and gait speed (m/s), and physical functioning by NYHA class and SF-36 physical functioning score. Activity was reported as mean time active/day across 30-days prior to enrolment (30-day PA). Multivariable regression methods were utilised to estimate associations between PA and frailty/functioning (OR = odds ratio, β = beta coefficient, CI = confidence intervals).ResultsData were available for 140 participants (median age 73, 70.7% male). Median 30-day PA across the analysis cohort was 134.9 min/day (IQR 60.8–195.9). PA was not significantly associated with Fried frailty status on multivariate analysis, however was associated with gait speed (β = 0.04, 95% CI 0.01–0.07, p = 0.01) and measures of physical functioning (NYHA class: OR 0.73, 95% CI 0.57–0.92, p = 0.01, SF-36 physical functioning: β = 4.60, 95% CI 1.38–7.83, p = 0.005).ConclusionsPA from cardiac devices was associated with physical functioning and gait speed. This highlights the importance of reviewing remote monitoring PA data to identify patients who could benefit from existing interventions. Further research should investigate how to embed this into clinical pathways.

1030-P: Feature Selection of Gait Measures Discriminating Prediabetes from Healthy Controls Using Machine Learning

1030-P: Feature Selection of Gait Measures Discriminating Prediabetes from Healthy Controls Using Machine Learning