Laboratory in a box: wearable sensors and its advantages for gait analysis

Game-based intradialytic non-weight-bearing exercise training on gait speed and balance in older adults with diabetes: a single-blind randomized controlled trial

Older adults with diabetes receiving hemodialysis have impaired gait speed and balance compared to the general population, which have been associated with increased risks of falls and mortality. This study evaluated the effectiveness of a game-based intradialytic exercise training program (iExergame) on improving gait speed and balance. This was a single-blind randomized controlled trial. The intervention group (IG) received iExergame training using real-time audiovisual feedback with wearable inertial sensors. The control group (CG) received conventional training without any technology. Both trainings were intradialytic, non-weight-bearing, and used ankle range of motion. Gait and balance parameters were collected at baseline and 4-week follow-up. Data from 70 adults (age 64.2 ± 9.0 years) were analyzed. Compared to the CG, the IG showed greater changes between baseline and 4-week follow-up in several parameters. Gait parameters included faster speeds and longer stride lengths, particularly during dual task walking (p < 0.050). Balance parameters included reductions in center of mass (p = 0.004), ankle (p < 0.001), and hip (p = 0.010) sways during semi-tandem stance, particularly in users of assistive devices. iExergame training could improve gait speed and balance in this population and might be an option to increase intradialytic exercise adherence while reducing burdens of exercise administration.

Inertial Sensor Location for Ground Reaction Force and Gait Event Detection Using Reservoir Computing in Gait

Inertial measurement units (IMUs) have shown promising outcomes for estimating gait event detection (GED) and ground reaction force (GRF). This study aims to determine the best sensor location for GED and GRF prediction in gait using data from IMUs for healthy and medial knee osteoarthritis (MKOA) individuals. In this study, 27 healthy and 18 MKOA individuals participated. Participants walked at different speeds on an instrumented treadmill. Five synchronized IMUs (Physilog®, 200 Hz) were placed on the lower limb (top of the shoe, heel, above medial malleolus, middle and front of tibia, and on medial of shank close to knee joint). To predict GRF and GED, an artificial neural network known as reservoir computing was trained using combinations of acceleration signals retrieved from each IMU. For GRF prediction, the best sensor location was top of the shoe for 72.2% and 41.7% of individuals in the healthy and MKOA populations, respectively, based on the minimum value of the mean absolute error (MAE). For GED, the minimum MAE value for both groups was for middle and front of tibia, then top of the shoe. This study demonstrates that top of the shoe is the best sensor location for GED and GRF prediction.

Comparison of a Wearable Accelerometer/Gyroscopic, Portable Gait Analysis System (LEGSYS+TM) to the Laboratory Standard of Static Motion Capture Camera Analysis

Examination of gait patterns has been used to determine severity, intervention triage and prognostic measures for many health conditions. Methods that generate detailed gait data for clinical use are typically logistically constrained to a formal gait laboratory setting. This has led to an interest in portable analysis systems for near clinical or community-based assessments. The following study assessed with the wearable accelerometer/gyroscopic, gait analysis system (LEGSYS+^TM) and the standard of static motion capture camera (MOCAP) analysis during a treadmill walk at three different walking speeds in healthy participants (n = 15). To compare each speed, 20 strides were selected from the MOCAP data and compared with the LEGSYS+ strides at the same time point. Both scatter and bland-Altman plots with accompanying linear regression analysis for each of the parameters. Each stride parameter showed minimal or a consistent difference between the LEGSYS+ and MOCAP, with the phase parameters showing inconsistencies between the systems. Overall, LEGSYS+ stride parameters can be used in the clinical setting, with the utility of phase parameters needing to be taken with caution.

Association between Fall History and Gait, Balance, Physical Activity, Depression, Fear of Falling, and Motor Capacity: A 6-Month Follow-Up Study

Maintaining function in older adults is key to the quality of life and longevity. This study examined the potential impact of falls on accelerating further deterioration over time in gait, balance, physical activity, depression, fear of falling, and motor capacity in older adults. 163 ambulatory older adults (age = 76.5 ± 7.7 years) participated and were followed for 6 months. They were classified into fallers or non-fallers based on a history of falling within the past year. At baseline and 6 months, all participants were objectively assessed for gait, balance, and physical activity using wearable sensors. Additional assessments included psychosocial concerns (depression and fear of falling) and motor capacity (Timed Up and Go test). The fallers showed lower gait performance, less physical activity, lower depression level, higher fear of falling, and less motor capacity than non-fallers at baseline and 6-month follow-up. Results also revealed acceleration in physical activity and motor capacity decline compared to non-fallers at a 6-month follow-up. Our findings suggest that falls would accelerate deterioration in both physical activity and motor performance and highlight the need for effective therapy to reduce the consequences of falls in older adults.

The application of artificial intelligence and custom algorithms with inertial wearable devices for gait analysis and detection of gait-altering pathologies in adults: A scoping review of literature

Background

The purpose of this scoping review was to explore the current applications of objective gait analysis using inertial measurement units, custom algorithms and artificial intelligence algorithms in detecting neurological and musculoskeletal gait altering pathologies from healthy gait patterns.

Methods

Literature searches were conducted of four electronic databases (Medline, PubMed, Embase and Web of Science) to identify studies that assessed the accuracy of these custom gait analysis models with inputs derived from wearable devices. Data was collected according to the preferred reporting items for systematic reviews and meta-analysis statement guidelines.

Results

A total of 23 eligible studies were identified for inclusion in the present review, including 10 custom algorithms articles and 13 artificial intelligence algorithms articles. Nine studies evaluated patients with Parkinson’s disease of varying severity and subtypes. Support vector machine was the commonest adopted artificial intelligence algorithm model, followed by random forest and neural networks. Overall classification accuracy was promising for articles that use artificial intelligence algorithms, with nine articles achieving more than 90% accuracy.

Conclusions

Current applications of artificial intelligence algorithms are reasonably effective discrimination between pathological and non-pathological gait. Of these, machine learning algorithms demonstrate the additional capacity to handle complicated data input, when compared to other custom algorithms. Notably, there has been increasing application of machine learning algorithms for conducting gait analysis. More studies are needed with unsupervised methods and in non-clinical settings to better reflect the community and home-based usage.

Digital Biomarkers of Cognitive Frailty: The Value of Detailed Gait Assessment Beyond Gait Speed

BACKGROUND

Cognitive frailty (CF), defined as the simultaneous presence of cognitive impairment and physical frailty, is a clinical symptom in early-stage dementia with promise in assessing the risk of dementia. The purpose of this study was to use wearables to determine the most sensitive digital gait biomarkers to identify CF.

METHODS

Of 121 older adults (age = 78.9 ± 8.2 years, body mass index = 26.6 ± 5.5 kg/m2) who were evaluated with a comprehensive neurological exam and the Fried frailty criteria, 41 participants (34%) were identified with CF and 80 participants (66%) were identified without CF. Gait performance of participants was assessed under single task (walking without cognitive distraction) and dual task (walking while counting backward from a random number) using a validated wearable platform. Participants walked at habitual speed over a distance of 10 m. A validated algorithm was used to determine steady-state walking. Gait parameters of interest include steady-state gait speed, stride length, gait cycle time, double support, and gait unsteadiness. In addition, speed and stride length were normalized by height.

RESULTS

Our results suggest that compared to the group without CF, the CF group had deteriorated gait performances in both single-task and dual-task walking (Cohen's effect size d = 0.42-0.97, p < 0.050). The largest effect size was observed in normalized dual-task gait speed (d = 0.97, p < 0.001). The use of dual-task gait speed improved the area under the curve (AUC) to distinguish CF cases to 0.76 from 0.73 observed for the single-task gait speed. Adding both single-task and dual-task gait speeds did not noticeably change AUC. However, when additional gait parameters such as gait unsteadiness, stride length, and double support were included in the model, AUC was improved to 0.87.

CONCLUSIONS

This study suggests that gait performances measured by wearable sensors are potential digital biomarkers of CF among older adults. Dual-task gait and other detailed gait metrics provide value for identifying CF above gait speed alone. Future studies need to examine the potential benefits of gait performances for early diagnosis of CF and/or tracking its severity over time.

Overground Walking in a Fully Immersive Virtual Reality: A Comprehensive Study on the Effects on Full-Body Walking Biomechanics

Virtual reality (VR) is an emerging technology offering tremendous opportunities to aid gait rehabilitation. To this date, real walking with users immersed in virtual environments with head-mounted displays (HMDs) is either possible with treadmills or room-scale (overground) VR setups. Especially for the latter, there is a growing interest in applications for interactive gait training as they could allow for more self-paced and natural walking. This study investigated if walking in an overground VR environment has relevant effects on 3D gait biomechanics. A convenience sample of 21 healthy individuals underwent standard 3D gait analysis during four randomly assigned walking conditions: the real laboratory (RLab), a virtual laboratory resembling the real world (VRLab), a small version of the VRlab (VRLab-), and a version which is twice as long as the VRlab (VRLab+). To immerse the participants in the virtual environment we used a VR-HMD, which was operated wireless and calibrated in a way that the virtual labs would match the real-world. Walking speed and a single measure of gait kinematic variability (GaitSD) served as primary outcomes next to standard spatio-temporal parameters, their coefficients of variant (CV%), kinematics, and kinetics. Briefly described, participants demonstrated a slower walking pattern (-0.09 ± 0.06 m/s) and small accompanying kinematic and kinetic changes. Participants also showed a markedly increased gait variability in lower extremity gait kinematics and spatio-temporal parameters. No differences were found between walking in VRLab+ vs. VRLab-. Most of the kinematic and kinetic differences were too small to be regarded as relevant, but increased kinematic variability (+57%) along with increased percent double support time (+4%), and increased step width variability (+38%) indicate gait adaptions toward a more conservative or cautious gait due to instability induced by the VR environment. We suggest considering these effects in the design of VR-based overground training devices. Our study lays the foundation for upcoming developments in the field of VR-assisted gait rehabilitation as it describes how VR in overground walking scenarios impacts our gait pattern. This information is of high relevance when one wants to develop purposeful rehabilitation tools.

Measuring Spatiotemporal Parameters on Treadmill Walking Using Wearable Inertial System

This study aims to measure and compare spatiotemporal gait parameters in nineteen subjects using a full wearable inertial mocap system Xsens (MVN Awinda, Netherlands) and a photoelectronic system one-meter OptoGaitTM (Microgait, Italy) on a treadmill imposing a walking speed of 5 km/h. A total of eleven steps were considered for each subject constituting a dataset of 209 samples from which spatiotemporal parameters (SPT) were calculated. The step length measurement was determined using two methods. The first one considers the calculation of step length based on the inverted pendulum model, while the second considers an anthropometric approach that correlates the stature with an anthropometric coefficient. Although the absolute agreement and consistency were found for the calculation of the stance phase, cadence and gait cycle, from our study, differences in SPT were found between the two systems. Mean square error (MSE) calculation of their speed (m/s) with respect to the imposed speed on a treadmill reveals a smaller error (MSE = 0.0008) using the OptoGaitTM. Overall, our results indicate that the accurate detection of heel strike and toe-off have an influence on phases and sub-phases for the entire acquisition. Future study in this domain should investigate how to design and integrate better products and algorithms aiming to solve the problematic issues already identified in this study without limiting the user's need and performance in a different environment.

Monitoring Symptoms of Infectious Diseases: Perspectives for Printed Wearable Sensors

Infectious diseases possess a serious threat to the world's population, economies, and healthcare systems. In this review, we cover the infectious diseases that are most likely to cause a pandemic according to the WHO (World Health Organization). The list includes COVID-19, Crimean-Congo Hemorrhagic Fever (CCHF), Ebola Virus Disease (EBOV), Marburg Virus Disease (MARV), Lassa Hemorrhagic Fever (LHF), Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), Nipah Virus diseases (NiV), and Rift Valley fever (RVF). This review also investigates research trends in infectious diseases by analyzing published research history on each disease from 2000-2020 in PubMed. A comprehensive review of sensor printing methods including flexographic printing, gravure printing, inkjet printing, and screen printing is conducted to provide guidelines for the best method depending on the printing scale, resolution, design modification ability, and other requirements. Printed sensors for respiratory rate, heart rate, oxygen saturation, body temperature, and blood pressure are reviewed for the possibility of being used for disease symptom monitoring. Printed wearable sensors are of great potential for continuous monitoring of vital signs in patients and the quarantined as tools for epidemiological screening.

Evaluation of Motor and Cognitive Performance in People with Parkinson's Disease Using Instrumented Trail-Making Test

INTRODUCTION

Parkinson's disease (PD) progressively impairs motor and cognitive performance. The current tools to detect decline in motor and cognitive functioning are often impractical for busy clinics and home settings. To address the gap, we designed an instrumented trail-making task (iTMT) based on a wearable sensor (worn on the shin) with interactive game-based software installed on a tablet. The iTMT test includes reaching to 5 indexed circles, a combination of numbers (1-3) and letters (A&amp;B) randomly positioned inside target circles, in a sequential order, which virtually appears on a screen kept in front of the participants, by rotating one's ankle joint while standing and holding a chair for safety. By measuring time to complete iTMT task (iTMT time), iTMT enables quantifying cognitive-motor performance.

PURPOSE

This study's objective is to examine the feasibility of iTMT to detect early cognitive-motor decline in PDs.

METHOD

Three groups of volunteers, including 14 cognitively normal (CN) older adults, 14 PDs, and 11 mild cognitive impaireds (MCI), were recruited. Participants completed MoCA, 20 m walking test, and 3 trials of iTMT.

RESULTS

All participants enabled to complete iTMT with <3 min, indicating high feasibility. The average iTMT time for CN-Older, PD, and MCI participants were 20.9 ± 0.9 s, 32.3 ± 2.4 s, and 40.9 ± 4.5 s, respectively. After adjusting for age and education level, pairwise comparison suggested large effect sizes for iTMT between CN-older versus PD (Cohen's d = 1.7, p = 0.024) and CN-older versus MCI (d = 1.57, p < 0.01). Significant correlations were observed when comparing iTMT time with the gait speed (r = -0.4, p = 0.011) and MoCA score (r = -0.56, p < 0.01).

CONCLUSION

This study demonstrated the feasibility and early results supporting the potential application of iTMT to determine cognitive-motor and distinguishing individuals with MCI and PD from CN-older adults. Future studies are warranted to test the ability of iTMT to track its subtle changes over time.

Assessment of Selected Spatio-Temporal Gait Parameters on Subjects with Pronated Foot Posture on the Basis of Measurements Using OptoGait. A Case-Control Study

Walking is part of daily life and in asymptomatic subjects it is relatively easy. The physiology of walking is complex and when this complex control system fails, the risk of falls increases. As a result, gait disorders have a major impact on the older adult population and have increased in frequency as a result of population aging. Therefore, the OptoGait sensor is intended to identify gait imbalances in pronating feet to try to prevent falling and injury by compensating for it with treatments that normalize such alteration. This study is intended to assess whether spatiotemporal alterations occur in the gait cycle in a young pronating population (cases) compared to a control group (non-pronating patients) analyzed with OptoGait. Method: a total of n = 142 participants consisting of n = 70 cases (pronators) and n = 72 healthy controls were studied by means of a 30 s treadmill program with a system of 96 OptoGait LED sensors. Results: Significant differences were found between the two groups and both feet in stride length and stride time, gait cycle duration and gait cadence (in all cases p < 0.05). Conclusions: pronating foot posture alters normal gait patterns measured by OptoGait; this finding presents imbalance in gait as an underlying factor. Prevention of this alteration could be considered in relation to its relationship to the risk of falling in future investigations.

How gait influences frailty models and health-related outcomes in clinical-based and population-based studies: a systematic review

Aging is often associated with a decline in physical function that eventually leads to loss of autonomy in activities of daily living (ADL). Walking is a very common ADL, important for main determinants of quality of life in older age, and it requires the integration of many physiological systems. Gait speed has been described as the 'sixth vital sign' because it is a core indicator of health and function in aging and disease. We reviewed original studies up to June 2020 that assessed frailty in both longitudinal and cross-sectional observational studies, paying particular attention to how gait is measured in older population and how the gait parameter adopted may influence the estimated frailty models and the health-related outcomes of the various studies (i.e. clinical, cognitive, physical, and nutritional outcomes). Eighty-five studies met the search strategy and were included in the present systematic review. According to the frailty tools, more than 60% of the studies used the physical phenotype model proposed by Fried and colleagues, while one-third referred to multi-domain indexes or models and only 5% referred to other single-domain frailty models (social or cognitive). The great heterogeneity observed in gait measurements and protocols limited the possibility to directly compare the results of the studies and it could represent an important issue causing variability in the different outcome measures in both clinical-and population-based settings. Gait appeared to be an indicator of health and function also in frail older adults, and different gait parameters appeared to predict adverse health-related outcomes in clinical, cognitive, and physical domains and, to a lesser extent, in nutritional domain. Gait has the potential to elucidate the common basic mechanisms of cognitive and motor decline. Advances in technology may extend the validity of gait in different clinical settings also in frail older adults, and technology-based assessment should be encouraged. Combining various gait parameters may enhance frailty prediction and classification of different frailty phenotypes.

Harnessing digital health to objectively assess cancer-related fatigue: The impact of fatigue on mobility performance

Objective

Cancer-related fatigue (CRF) is highly prevalent among cancer survivors, which may have long-term effects on physical activity and quality of life. CRF is assessed by self-report or clinical observation, which may limit timely diagnosis and management. In this study, we examined the effect of CRF on mobility performance measured by a wearable pendant sensor.

Methods

This is a secondary analysis of a clinical trial evaluating the benefit of exercise in cancer survivors with chemotherapy-induced peripheral neuropathy (CIPN). CRF status was classified based on a Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) score ≤ 33. Among 28 patients (age = 65.7±9.8 years old, BMI = 26.9±4.1kg/m², sex = 32.9%female) with database variables of interest, twenty-one subjects (75.9%) were classified as non-CRF. Mobility performance, including behavior (sedentary, light, and moderate to vigorous activity (MtV)), postures (sitting, standing, lying, and walking), and locomotion (e.g., steps, postural transitions) were measured using a validated pendant-sensor over 24-hours. Baseline psychosocial, Functional Assessment of Cancer Therapy–General (FACT-G), Falls Efficacy Scale–International (FES-I), and motor-capacity assessments including gait (habitual speed, fast speed, and dual-task speed) and static balance were also performed.

Results

Both groups had similar baseline clinical and psychosocial characteristics, except for body-mass index (BMI), FACT-G, FACIT-F, and FES-I (p<0.050). The groups did not differ on motor-capacity. However, the majority of mobility performance parameters were different between groups with large to very large effect size, Cohen’s d ranging from 0.91 to 1.59. Among assessed mobility performance, the largest effect sizes were observed for sedentary-behavior (d = 1.59, p = 0.006), light-activity (d = 1.48, p = 0.009), and duration of sitting+lying (d = 1.46, p = 0.016). The largest correlations between mobility performance and FACIT-F were observed for sitting+lying (rho = -0.67, p<0.001) and the number of steps per day (rho = 0.60, p = 0.001).

Conclusion

The results of this study suggest that sensor-based mobility performance monitoring could be considered as a potential digital biomarker for CRF assessment. Future studies warrant evaluating utilization of mobility performance to track changes in CRF over time, response to CRF-related interventions, and earlier detection of CRF.

Concurrent Validity, Test-Retest Reliability, and Sensitivity to Change of a Single Body-Fixed Sensor for Gait Analysis during Rollator-Assisted Walking in Acute Geriatric Patients

Body-fixed sensor (BFS) technology offers portable, low-cost and easy-to-use alternatives to laboratory-bound equipment for analyzing an individual's gait. Psychometric properties of single BFS systems for gait analysis in older adults who require a rollator for walking are, however, unknown. The study's aim was to evaluate the concurrent validity, test-retest-reliability, and sensitivity to change of a BFS (DynaPort MoveTest; McRoberts B.V., The Hague, The Netherlands) for measuring gait parameters during rollator-assisted walking. Fifty-eight acutely hospitalized older patients equipped with the BFS at the lower back completed a 10 m walkway using a rollator. Concurrent validity was assessed against the Mobility Lab (APDM Inc.; Portland, OR, USA), test-retest reliability over two trials within a 15 min period, and sensitivity to change in patients with improved, stable and worsened 4 m usual gait speed over hospital stay. Bland-Altman plots and intraclass correlation coefficients (ICC) for gait speed, cadence, step length, step time, and walk ratio indicate good to excellent agreement between the BFS and the Mobility Lab (ICC_2,1 = 0.87-0.99) and the repeated trials (ICC_2,1 = 0.83-0.92). Moderate to large standardized response means were observed in improved (gait speed, cadence, step length, walk ratio: 0.62-0.99) and worsened patients (gait speed, cadence, step time: -0.52 to -0.85), while those in stable patients were trivial to small (all gait parameters: -0.04-0.40). The BFS appears to be a valid, reliable and sensitive instrument for measuring spatio-temporal gait parameters during rollator-assisted walking in geriatric patients.

Gait Analysis in a Box: A System Based on Magnetometer-Free IMUs or Clusters of Optical Markers with Automatic Event Detection

Gait analysis based on full-body motion capture technology (MoCap) can be used in rehabilitation to aid in decision making during treatments or therapies. In order to promote the use of MoCap gait analysis based on inertial measurement units (IMUs) or optical technology, it is necessary to overcome certain limitations, such as the need for magnetically controlled environments, which affect IMU systems, or the need for additional instrumentation to detect gait events, which affects IMUs and optical systems. We present a MoCap gait analysis system called Move Human Sensors (MH), which incorporates proposals to overcome both limitations and can be configured via magnetometer-free IMUs (MH-IMU) or clusters of optical markers (MH-OPT). Using a test-retest reliability experiment with thirty-three healthy subjects (20 men and 13 women, 21.7 ± 2.9 years), we determined the reproducibility of both configurations. The assessment confirmed that the proposals performed adequately and allowed us to establish usage considerations. This study aims to enhance gait analysis in daily clinical practice.

Attentional prioritization in dual-task walking: Effects of stroke, environment, and instructed focus

BACKGROUND

The impact of high distraction, real-world environments on dual-task interference and flexibility of attentional prioritization during dual-task walking in people with stroke is unknown.

RESEARCH QUESTION

How does a real-world environment affect dual-task performance and flexible task prioritization during dual-task walking in adults with and without stroke?

METHODS

Adults with stroke (n = 29) as well as age-, gender-, and education-matched adults without stroke (n = 23) participated. Single and dual-task walking were examined in two different environments (lab hallway, hospital lobby). Two different dual-task combinations were assessed (Stroop-gait, speech-gait). Each dual-task was performed first without explicit instruction about task prioritization (no-priority) and then with gait-priority instruction and Stroop/speech-priority instruction in randomized order.

RESULTS

People with stroke had significantly slower dual-task gait speed (Stroop only) in the lobby than the lab, but the effect was not clinically meaningful. Stroop reaction time for all participants was also slower in the lobby than the lab. All participants slowed their walking speed while generating spontaneous speech, but this effect was not influenced by environment. The dual-task attention allocation strategy was generally inflexible to instructed prioritization in adults with and without stroke in both environments, however, the volitional attention allocation strategy differed for the two dual-task conditions such that speech was prioritized in the speech-gait dual-task and gait appeared to be prioritized in the Stroop-gait dual-task.

SIGNIFICANCE

Although dual-tasking slows walking speed and verbal responses to auditory stimuli in people with stroke, the effects are not considerably impacted by a more complex, distracting environment. Adults with and without stroke may have difficulty overriding the preferred attention allocation strategy during dual-task walking, especially for habitual dual-tasks such as walking while speaking. It may also be that the cognitive control strategy governing task prioritization is influenced by degree of cognitive engagement.

The impact of diabetic foot ulcers and unilateral offloading footwear on gait in people with diabetes

BACKGROUND

Unilateral offloading footwear prescribed to patients with diabetic foot ulcers elevates one limb relative to the other, which may lead to limp and abnormal gait. This study investigated whether the unilateral foot ulcer and offloading combination negatively impacts gait function beyond diabetic peripheral neuropathy.

METHODS

Eighty-six participants were recruited in 3 groups: 12 with diabetic peripheral neuropathy and unilateral foot ulcers wearing offloading footwear (offloading group, age = 55.6 ± 9.5 years, BMI = 30.9 ± 4.5 kg/m2), 27 with diabetic peripheral neuropathy (neuropathy group, age = 64.3 ± 7.7 years, BMI = 30.9 ± 5.4 kg/m2), and 47 non-diabetic controls (non-diabetic group, age = 62.9 ± 16.1 years, BMI = 29.0 ± 6.0 kg/m2). Gait function was quantified during a habitual speed walking test using a validated wearable platform.

FINDINGS

The offloading group exhibited deteriorated gait function compared to the non-diabetic group (p < 0.005, Cohen's effect size d = 0.90-2.61). They also had decreased gait speed (p < 0.001, d = 1.79) and stride length (p < 0.001, d = 1.76), as well as increased gait cycle time (p < 0.001, d = 1.67) and limp (p < 0.050, d = 0.72-1.49) compared to the neuropathy group. The offloading group showed increased gait unsteadiness compared to the neuropathy group, but the difference did not reach statistical significance in our samples.

INTERPRETATION

This study demonstrated that while diabetic peripheral neuropathy deteriorates gait function, including increasing gait unsteadiness and limp, the diabetic foot ulcer and offloading combination magnifies the deterioration beyond diabetic peripheral neuropathy. These findings promote caution of the current standards of care for treating diabetic foot ulcers with offloading footwear. However, it is possible that a contralateral shoe lift may remedy deteriorated gait function and improve quality of life for unilateral offloading users.

Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Inertial measurement unit systems are wearable sensors that can measure the movement of a human in real-time with relatively little space and high portability. The purpose of this study was to investigate the accuracy of the inertial measurement unit (IMU) system for gait analysis by comparing it with measurements obtained using an optical motion capture (OMC) system. To compare the accuracies of these two different motion capture systems, the Spatio-temporal and kinematic parameters were measured in young adults during normal walking. Thirty healthy participants participated in the study. Data were collected while walking 5 strides on a 7 m walkway at a self-selected speed. Results of gait analysis showed that the Spatio-temporal (stride time, stride length, cadence, step length) and kinematic (knee joint peak to peak of movement) parameters were not significantly different in the participant. Spatio-temporal and kinematic parameters of the two systems were compared using the Bland–Altman method. The results obtained showed that the measurements of Spatio-temporal and kinematic parameters of gait by the two systems were similar, which suggested that IMU and OMC systems could be used interchangeably for gait measurements. Therefore, gait analysis performed using the wearable IMU system might efficiently provide gait measurements and enable accurate analysis.

Using wearables to screen motor performance deterioration because of cancer and chemotherapy-induced peripheral neuropathy (CIPN) in adults - Toward an early diagnosis of CIPN

OBJECTIVE

An essential component for optimizing quality of life in adults with cancer is determining the degree to which therapy may negatively impact motor-performance, so that patients can maintain their quality of life and independence. This study examined whether instrumented gait and balance could determine the magnitude of deterioration in motor-performance from chemotherapy-induced peripheral neuropathy (CIPN).

METHODS

We recruited 84 adults with cancer (age = 71.1 ± 9.7 years old, BMI = 26.8 ± 6.2 kg/m², gender = 56%female) and 57 age-matched non-cancer patients (age = 69.5 ± 9.8 years old, BMI = 27.1 ± 6.0 kg/m², gender = 79%female). Based on clinical screening, the group with cancer was classified into two groups: participants with CIPN (CIPN+) and without CIPN (CIPN-). Gait and balance were quantified using validated wearables. The Vibration Perception Threshold (VPT) test was used to stratify the CIPN+ group into mild (Mild-CIPN) and severe (Severe-CIPN) subgroups.

RESULTS

All gait and balance parameters were deteriorated in the group with cancer compared to non-cancer group with the largest effects observed for stride-time (11%, Cohen's effect size d = 1.00, p < 0.001) and eyes-closed ankle sway (94%, d = 0.49, p = 0.001). The same trend was observed when the Severe-CIPN subgroup was compared to the Mild-CIPN. VPT correlates significantly with motor deterioration, with the largest correlation found in stride-time (Rho = 0.37, p = 0.007). Severe-CIPN subjects were significantly older and overall had more deterioration in the majority of motor-performance parameters after adjusting for age (p < 0.050).

CONCLUSION

These results confirmed the negative impact of CIPN on motor-performance with the largest effects on ankle stability and stride-time. VPT is a predictor of motor deterioration and may be used to determine the severity of CIPN symptom.

Indirect Measurement of Ground Reaction Forces and Moments by Means of Wearable Inertial Sensors: A Systematic Review

In the last few years, estimating ground reaction forces by means of wearable sensors has come to be a challenging research topic paving the way to kinetic analysis and sport performance testing outside of labs. One possible approach involves estimating the ground reaction forces from kinematic data obtained by inertial measurement units (IMUs) worn by the subject. As estimating kinetic quantities from kinematic data is not an easy task, several models and protocols have been developed over the years. Non-wearable sensors, such as optoelectronic systems along with force platforms, remain the most accurate systems to record motion. In this review, we identified, selected and categorized the methodologies for estimating the ground reaction forces from IMUs as proposed across the years. Scopus, Google Scholar, IEEE Xplore, and PubMed databases were interrogated on the topic of Ground Reaction Forces estimation based on kinematic data obtained by IMUs. The identified papers were classified according to the methodology proposed: (i) methods based on direct modelling; (ii) methods based on machine learning. The methods based on direct modelling were further classified according to the task studied (walking, running, jumping, etc.). Finally, we comparatively examined the methods in order to identify the most reliable approaches for the implementation of a ground reaction force estimator based on IMU data.

Toward Smart Footwear to Track Frailty Phenotypes-Using Propulsion Performance to Determine Frailty

Frailty assessment is dependent on the availability of trained personnel and it is currently limited to clinic and supervised setting. The growing aging population has made it necessary to find phenotypes of frailty that can be measured in an unsupervised setting for translational application in continuous, remote, and in-place monitoring during daily living activity, such as walking. We analyzed gait performance of 161 older adults using a shin-worn inertial sensor to investigate the feasibility of developing a foot-worn sensor to assess frailty. Sensor-derived gait parameters were extracted and modeled to distinguish different frailty stages, including non-frail, pre-frail, and frail, as determined by Fried Criteria. An artificial neural network model was implemented to evaluate the accuracy of an algorithm using a proposed set of gait parameters in predicting frailty stages. Changes in discriminating power was compared between sensor data extracted from the left and right shin sensor. The aim was to investigate the feasibility of developing a foot-worn sensor to assess frailty. The results yielded a highly accurate model in predicting frailty stages, irrespective of sensor location. The independent predictors of frailty stages were propulsion duration and acceleration, heel-off and toe-off speed, mid stance and mid swing speed, and speed norm. The proposed model enables discriminating different frailty stages with area under curve ranging between 83.2–95.8%. Furthermore, results from the neural network suggest the potential of developing a single-shin worn sensor that would be ideal for unsupervised application and footwear integration for continuous monitoring during walking.

Foot Problems in Older Adults Associations with Incident Falls, Frailty Syndrome, and Sensor-Derived Gait, Balance, and Physical Activity Measures

BACKGROUND

Research on foot problems and frailty is sparse and could advance using wearable sensor-based measures of gait, balance, and physical activity (PA). This study examined the effect of foot problems on the likelihood of falls, frailty syndrome, motor performance, and PA in community-dwelling older adults.

METHODS

Arizona Frailty Cohort Study participants (community-dwelling adults aged ≥65 years without baseline cognitive deficit, severe movement disorders, or recent stroke) underwent Fried frailty and foot assessment. Gait, balance (bipedal eyes open and eyes closed), and spontaneous PA over 48 hours were measured using validated wearable sensor technologies.

RESULTS

Of 117 participants, 41 (35%) were nonfrail, 56 (48%) prefrail, and 20 (17%) frail. Prevalence of foot problems (pain, peripheral neuropathy, or deformity) increased significantly as frailty category worsened (any problem: 63% in nonfrail, 80% in prefrail [odds ratio (OR) = 2.0], and 95% in frail [OR = 8.3]; P = .03 for trend) due to associations between foot problems and both weakness and exhaustion. Foot problems were associated with fear of falling but not with fall history or incident falls over 6 months. Foot pain and peripheral neuropathy were associated with lower gait speed and stride length; increased double support time; increased mediolateral sway of center of mass during walking, age adjusted; decreased eyes open sway of center of mass and ankle during quiet standing, age adjusted; and lower percentage walking, percentage standing, and total steps per day.

CONCLUSIONS

Foot problems were associated with frailty level and decreased motor performance and PA. Wearable technology is a practical way to screen for deterioration in gait, balance, and PA that may be associated with foot problems. Routine assessment and management of foot problems could promote earlier intervention to retain motor performance and manage fear of falling in older adults, which may ultimately improve healthy aging and reduce risk of frailty.

Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis

Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically evaluates advanced gait and balance analysis technologies and their applicability to identifying early lower limb dysfunction in people with MS. Non-wearable (motion capture systems, force platforms, and sensor-embedded walkways) and wearable (pressure and inertial sensors) biomechanical analysis systems have been developed to provide quantitative gait and balance assessments. Non-wearable systems are highly accurate, reliable and provide detailed outcomes, but require cumbersome and expensive equipment. Wearable systems provide less detail but can be used in community settings and can provide real-time feedback to patients and clinicians. Biomechanical analysis using advanced gait and balance analysis technologies can identify changes in gait and balance in early MS and consequently have the potential to significantly improve monitoring of mobility changes in MS.

A practical step length algorithm using lower limb angular velocities

The use of Inertial Measurement Units (IMUs) for spatial gait analysis has opened the door to unconstrained measurements within the home and community. Bandwidth, cost limitations, and ease of use has historically restricted the number and location of sensors worn on the body. In this paper, we describe a four-sensor configuration of IMUs placed on the shanks and thighs that is sufficient to provide an accurate measure of temporal gait parameters, spatial gait parameters, and joint angle dynamics during ambulation. Estimating spatial gait parameters solely from gyroscope data is preferred because gyroscopes are less susceptible to sensor noise and a system comprised of only gyroscopes uses decreased bandwidth compared to a typical 9 degree-of-freedom IMU. The purpose of this study was to determine the validity of a novel method of step length estimation using gyroscopes attached to the shanks and thighs. An Inverted Pendulum Model algorithm (IPM) was proposed to calculate step length, stride length, and gait speed. The algorithm incorporates heel-strike events and average forward velocity per step to make these assessments. IMU algorithm accuracy was determined via concurrent validity with an instrumented walkway and results explained via the collision model of gait. The IPM produced accurate estimates of step length, stride length, and gait speed with a mean difference of 3 cm and an RMSE of 6.6 cm for step length, thus establishing a new approach for spatial gait parameter calculation. The lack of numerical integration in IPM makes it well suited for use in continuous monitoring applications where sensor sampling rates are restricted.

Wearable sensors objectively measure gait parameters in Parkinson's disease

Distinct gait characteristics like short steps and shuffling gait are prototypical signs commonly observed in Parkinson's disease. Routinely assessed by observation through clinicians, gait is rated as part of categorical clinical scores. There is an increasing need to provide quantitative measurements of gait, e.g. to provide detailed information about disease progression. Recently, we developed a wearable sensor-based gait analysis system as diagnostic tool that objectively assesses gait parameter in Parkinson's disease without the need of having a specialized gait laboratory. This system consists of inertial sensor units attached laterally to both shoes. The computed target of measures are spatiotemporal gait parameters including stride length and time, stance phase time, heel-strike and toe-off angle, toe clearance, and inter-stride variation from gait sequences. To translate this prototype into medical care, we conducted a cross-sectional study including 190 Parkinson's disease patients and 101 age-matched controls and measured gait characteristics during a 4x10 meter walk at the subjects' preferred speed. To determine intraindividual changes in gait, we monitored the gait characteristics of 63 patients longitudinally. Cross-sectional analysis revealed distinct spatiotemporal gait parameter differences reflecting typical Parkinson's disease gait characteristics including short steps, shuffling gait, and postural instability specific for different disease stages and levels of motor impairment. The longitudinal analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson's disease and corresponded to physician ratings. Taken together, we successfully show that wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson's disease. These data demonstrate the feasibility and applicability of objective wearable sensor-based gait measurement in Parkinson's disease reaching high technological readiness levels for both, large scale clinical studies and individual patient care.

Measurement of Walking Ground Reactions in Real-Life Environments: A Systematic Review of Techniques and Technologies

Monitoring natural human gait in real-life environments is essential in many applications, including quantification of disease progression, monitoring the effects of treatment, and monitoring alteration of performance biomarkers in professional sports. Nevertheless, developing reliable and practical techniques and technologies necessary for continuous real-life monitoring of gait is still an open challenge. A systematic review of English-language articles from scientific databases including Scopus, ScienceDirect, Pubmed, IEEE Xplore, EBSCO and MEDLINE were carried out to analyse the ‘accuracy’ and ‘practicality’ of the current techniques and technologies for quantitative measurement of the tri-axial walking ground reactions outside the laboratory environment, and to highlight their strengths and shortcomings. In total, 679 relevant abstracts were identified, 54 full-text papers were included in the paper and the quantitative results of 17 papers were used for meta-analysis and comparison. Three classes of methods were reviewed: (1) methods based on measured kinematic data; (2) methods based on measured plantar pressure; and (3) methods based on direct measurement of ground reactions. It was found that all three classes of methods have competitive accuracy levels with methods based on direct measurement of the ground reactions showing highest accuracy while being least practical for long-term real-life measurement. On the other hand, methods that estimate ground reactions using measured body kinematics show highest practicality of the three classes of methods reviewed. Among the most prominent technical and technological challenges are: (1) reducing the size and price of tri-axial load-cells; (2) improving the accuracy of orientation measurement using IMUs; (3) minimizing the number and optimizing the location of required IMUs for kinematic measurement; (4) increasing the durability of pressure insole sensors, and (5) enhancing the robustness and versatility of the ground reactions estimation methods to include pathological gaits and natural variability of gait in real-life physical environment.

Biomechanical Effects of Prefabricated Foot Orthoses and Rocker-Sole Footwear in Individuals With First Metatarsophalangeal Joint Osteoarthritis

Objective

To evaluate the effects of prefabricated foot orthoses and rocker‐sole footwear on spatiotemporal parameters, hip and knee kinematics, and plantar pressures in people with first metatarsophalangeal (MTP) joint osteoarthritis (OA). Methods. A total of 102 people with first MTP joint OA were randomly allocated to receive prefabricated foot orthoses or rocker‐sole footwear. The immediate biomechanical effects of the interventions (compared to usual footwear) were examined using a wearable sensor motion analysis system and an in‐shoe plantar pressure measurement system.

Results

Spatiotemporal/kinematic and plantar pressure data were available from 88 and 87 participants, respectively. The orthoses had minimal effect on spatiotemporal or kinematic parameters, while the rocker‐sole footwear resulted in reduced cadence, percentage of the gait cycle spent in stance phase, and sagittal plane hip range of motion. The orthoses increased peak pressure under the midfoot and lesser toes. Both interventions significantly reduced peak pressure under the first MTP joint, and the rocker‐sole shoes also reduced peak pressure under the second through fifth MTP joints and heel. When the effects of the orthoses and rocker‐sole shoes were directly compared, there was no difference in peak pressure under the hallux, first MTP joint, or heel; however, the rocker‐sole shoes exhibited lower peak pressure under the lesser toes, second through fifth MTP joints, and midfoot.

Conclusion

Prefabricated foot orthoses and rocker‐sole footwear are effective at reducing peak pressure under the first MTP joint in people with first MTP joint OA, but achieve this through different mechanisms. Further research is required to determine whether these biomechanical changes result in improvements in symptoms.

Alterations in gait parameters with peripheral artery disease: The importance of pre-frailty as a confounding variable

Although poor walking is the most common symptom of peripheral artery disease (PAD), reported results are inconsistent when comparing gait parameters between PAD patients and healthy controls. This inconsistency may be due to frailty, which is highly prevalent among PAD patients. To address this hypothesis, 41 participants, 17 PAD (74±8 years) and 24 aged-matched controls (76±7 years), were recruited. Gait was objectively assessed using validated wearable sensors. Analysis of covariate (ANCOVA) tests were used to compare gait parameters between PAD and non-PAD groups, considering age, gender, and body mass index as covariates, while stratified based on frailty status. According to the Fried frailty index, 47% of PAD and 50% of control participants were non-frail and the rest were classified as pre-frail. Within non-frail participants, gait speed, body sway during walking, stride length, gait cycle time, double-support, knee range of motion, speed variability, mid-swing speed, and gait initiation were significantly different between PAD and control groups (effect size d = 0.75±0.43). In the pre-frail group, however, most of the gait differences were diminished except for gait initiation and gait variability. Results suggest that gait initiation is the most sensitive parameter for detecting gait impairment in PAD participants when compared to controls, regardless of frailty status (d = 1.30-1.41; p<0.050). The observed interaction effect between frailty and PAD on gait parameters confirms the importance of assessing functionality in addition to age to provide more consistency in detecting motor performance impairments due to PAD.

Validity and reliability of a portable gait analysis system for measuring spatiotemporal gait characteristics: comparison to an instrumented treadmill

BACKGROUND

Gait analysis serves as an important tool for clinicians and other health professionals to assess gait patterns related to functional limitations due to neurological or orthopedic conditions. The purpose of this study was to assess the validity of a body-worn inertial sensor system (RehaGait®) for measuring spatiotemporal gait characteristics compared to a stationary treadmill (Zebris) and the reliability of both systems at different walking speeds and slopes.

METHODS

Gait analysis was performed during treadmill walking at different speeds (habitual walking speed (normal speed); 15 % above normal walking speed; 15 % below normal walking speed) and slopes (0 % slope; 15 % slope) in 22 healthy participants twice 1 week apart. Walking speed, stride length, cadence and stride time were computed from the inertial sensor system and the stationary treadmill and compared using repeated measures analysis of variance. Effect sizes of differences between systems were assessed using Cohen's d, and limits of agreement and systematic bias were computed.

RESULTS

The RehaGait® system slightly overestimated stride length (+2.7 %) and stride time (+0.8 %) and underestimate cadence (-1.5 %) with small effect sizes for all speeds and slopes (Cohen's d ≤ 0.44) except slow speed at 15 % slope (Cohen's d > 0.80). Walking speed obtained with the RehaGait® system closely matched the speed set on the treadmill tachometer. Intraclass correlation coefficients (ICC) were excellent for speed, cadence and stride time and for stride length at normal and fast speed at 0 % slope (ICC: .91-1.00). Good ICC values were found for stride length at slow speed at 0 % slope and all speeds at 15 % slope (ICC: .73-.90). Both devices had excellent reliability for most gait characteristics (ICC: .91-1.00) except good reliability for the RehaGait® for stride length at normal and fast speed at 0 % slope and at slow speed at 15 % slope (ICC: .80-.87).

CONCLUSIONS

Larger limits of agreement for walking at 15 % slope suggests that uphill walking may influence the reliability of the RehaGait® system. The RehaGait® is a valid and reliable tool for measuring spatiotemporal gait characteristics during level and inclined treadmill walking.

Spatiotemporal gait parameters during dual task walking in need of care elderly and young adults. A cross-sectional study

BACKGROUND

Up to now there have only been marginal data in the elderly in need of care regarding spatiotemporal gait parameters during single (ST) and dual tasking (DT).

AIM

The aim of this study was to allocate data for gait speed, cadence and stride length cycle variability in the elderly in need of care and in young adults during ST and DT, to compare the two groups and to demonstrate the impact of ST and DT on gait parameters.

MATERIAL AND METHODS

This cross-sectional study investigated a group of 16 young healthy adults (mean age 23.0 ± 2.5 years) and a group of 16 elderly persons in need of care (mean age 85.5 ± 0.6 years). The RehaWatch system was used to collect the spatiotemporal gait parameters cadence, speed and stride length. The participants completed four different measurements during normal walking and fast walking during ST and DT over a walking distance of 20 m. The Wilcoxon rank sum test and Whitney-U test were used for statistical analysis.

RESULTS

Gait speed (ST and DT: p < 0.001), cadence (ST and DT: p < 0.001) and gait variability (ST: p = 0.007, DT: p = 0.003) were significantly reduced in the elderly in need of care group compared to the young group. The gait speed in the elderly in need of care group decreased from normal to fast walking (ST = - 2.8%, DT = - 12.2%) compared to the young group (ST = 31.5%, DT = 25.2%).

CONCLUSION

The results of this study are comparable with the results of existing studies, which investigated falling and non-falling participants. Elderly people in need of care cannot increase the normal gait speed.

Wearable sensor-based in-home assessment of gait, balance, and physical activity for discrimination of frailty status: baseline results of the Arizona frailty cohort study

BACKGROUND

Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed.

OBJECTIVE

To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail).

METHODS

In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n=44, prefrail: n=60, frail: n=21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels.

RESULTS

Gait speed (area under the curve, AUC=0.802), hip sway (AUC=0.734), and steps/day (AUC=0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC=0.857) and double support (AUC=0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC=0.818). No balance parameter discriminated between three frailty levels.

CONCLUSION

Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.

Wearable sensor-based in-home assessment of gait, balance, and physical activity for discrimination of frailty status: baseline results of the Arizona frailty cohort study

BACKGROUND

Frailty is a geriatric syndrome resulting from age-related cumulative decline across multiple physiologic systems, impaired homeostatic reserve, and reduced capacity to resist stress. Based on recent estimates, 10% of community-dwelling older individuals are frail and another 41.6% are prefrail. Frail elders account for the highest health care costs in industrialized nations. Impaired physical function is a major indicator of frailty, and functional performance tests are useful for the identification of frailty. Objective instrumented assessments of physical functioning that are feasible for home frailty screening have not been adequately developed.

OBJECTIVE

To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail).

METHODS

In an observational cross-sectional study, in-home visits were completed in 125 older adults (nonfrail: n=44, prefrail: n=60, frail: n=21) living in Tucson, Ariz., USA, between September 2012 and November 2013. Temporal-spatial gait parameters (speed, stride length, stride time, double support, and variability of stride velocity), postural balance (sway of hip, ankle, and center of mass), and PA (percentage of walking, standing, sitting, and lying; mean duration and variability of single walking, standing, sitting, and lying bouts) were measured in the participant's home using validated wearable sensor technology. Logistic regression was used to assess the most sensitive gait, balance, and PA variables for identifying prefrail participants (vs. nonfrail). Multinomial logistic regression was used to identify variables sensitive to discriminate between three frailty levels.

RESULTS

Gait speed (area under the curve, AUC=0.802), hip sway (AUC=0.734), and steps/day (AUC=0.736) were the most sensitive parameters for the identification of prefrailty. Multinomial regression revealed that stride length (AUC=0.857) and double support (AUC=0.841) were the most sensitive gait parameters for discriminating between three frailty levels. Interestingly, walking bout duration variability was the most sensitive PA parameter for discriminating between three frailty levels (AUC=0.818). No balance parameter discriminated between three frailty levels.

CONCLUSION

Our results indicate that unique parameters derived from objective assessment of gait, balance, and PA are sensitive for the identification of prefrailty and the classification of a subject's frailty level. The present findings highlight the potential of wearable sensor technology for in-home assessment of frailty status.

Clinical evaluation of a mobile sensor-based gait analysis method for outcome measurement after knee arthroplasty

Clinical scores and motion-capturing gait analysis are today's gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients' actual quality of life has been questioned. In this context, mobile gait analysis systems have been introduced to overcome some of these limitations. This study used a previously developed mobile gait analysis system comprising three inertial sensor units to evaluate daily activities and sports. The sensors were taped to the lumbosacral junction and the thigh and shank of the affected limb. The annotated raw data was evaluated using our validated proprietary software. Six patients undergoing knee arthroplasty were examined the day before and 12 months after surgery. All patients reported a satisfactory outcome, although four patients still had limitations in their desired activities. In this context, feasible running speed demonstrated a good correlation with reported impairments in sports-related activities. Notably, knee flexion angle while descending stairs and the ability to stop abruptly when running exhibited good correlation with the clinical stability and proprioception of the knee. Moreover, fatigue effects were displayed in some patients. The introduced system appears to be suitable for outcome measurement after knee arthroplasty and has the potential to overcome some of the limitations of stationary gait labs while gathering additional meaningful parameters regarding the force limits of the knee.

Improvements in gait characteristics after intensive resistance and functional training in people with dementia: a randomised controlled trial

BACKGROUND

Preventing and rehabilitating gait disorders in people with dementia during early disease stage is of high importance for staying independent and ambulating safely. However, the evidence gathered in randomized controlled trials (RCTs) on the effectiveness of exercise training for improving spatio-temporal gait parameters in people with dementia is scarce. The aim of the present study was to determine whether a specific, standardized training regimen can improve gait characteristics in people with dementia.

METHODS

Sixty-one individuals (mean age: 81.9 years) with confirmed mild to moderate stage dementia took part in a 3-month double-blinded outpatient RCT. Subjects in the intervention group (IG) received supervised, progressive resistance and functional group training for 3 months (2 times per week for two hours) specifically developed for people with dementia. Subjects in the control group (CG) conducted a low-intensity motor placebo activity program. Gait characteristics were measured before and after the intervention period using a computerized gait analysis system (GAITRite®).

RESULTS

Adherence to the intervention was excellent, averaging 91.9% in the IG and 94.4% in the CG. The exercise training significantly improved gait speed (P < 0.001), cadence (P = 0.002), stride length (P = 0.008), stride time (P = 0.001), and double support (P = 0.001) in the IG compared to the CG. Effect sizes were large for all gait parameters that improved significantly (Cohen's d: 0.80-1.27). No improvements were found for step width (P = 0.999), step time variability (P = 0.425) and Walk-Ratio (P = 0.554). Interestingly, low baseline motor status, but not cognitive status, predicted positive training response (relative change in gait speed from baseline).

CONCLUSION

The intensive, dementia-adjusted training was feasible and improved clinically meaningful gait variables in people with dementia. The exercise program may represent a model for preventing and rehabilitating gait deficits in the target group. Further research is required for improving specific gait characteristics such as gait variability in people with dementia.

TRIAL REGISTRATION

ISRCTN49243245.

Diabetic peripheral neuropathy and gait: does footwear modify this association?

BACKGROUND

Gait-related fall risk is the leading cause of mortality among patients with diabetes, especially those older than 65 years. Deterioration in balance and loss of protective sensation in lower extremities contribute significantly to fall risk in patients with diabetic peripheral neuropathy (DPN). This study aimed to explore the impact of neuropathy and foot ulcer on gait.

METHODS

We recruited 39 participants (age, 56.9 ± 8.2 years; body mass index, 29.6.3 ± 4.7 kg/m2), including 15 DPN patients without foot ulcers, 16 DPN patients with foot ulcers, and 8 healthy aged-matched controls. Patients with active foot ulcers wore an offloading device during gait examination, including removable cast walker.

RESULTS

Results suggest that neuropathy alters gait mainly by increasing gait initiation, gait variability (coefficient of variation of gait velocity), and double support (DS) time, while reducing knee range of motion and center of mass sway (p < .05). Interestingly, the presence of foot ulcer does not impact gait velocity (p > .1) but enhances some of the gait parameters such as gait variability and DS time.

CONCLUSIONS

This study demonstrates that neuropathy deteriorates gait, but the presence of foot ulcers does not alter gait parameters further than neuropathy. In addition, patients with foot ulcers demonstrated a better gait compared with DPN patients without ulcers. We speculate that offloading footwear may be enhancing the somatosensory feedback from sensate skin, thereby positively affecting gait parameters. A study with a larger sample is required to explore the effect of prescribed footwear in the DPN population in order to validate the findings of this research study.

Frailty and technology: a systematic review of gait analysis in those with frailty

BACKGROUND

New technologies for gait assessment are emerging and have provided new avenues for accurately measuring gait characteristics in home and clinic. However, potential meaningful clinical gait parameters beyond speed have received little attention in frailty research.

OBJECTIVE

To study gait characteristics in different frailty status groups for identifying the most useful parameters and assessment protocols for frailty diagnosis.

METHODS

We searched PubMed, Embase, PsycINFO, CINAHL, Web of Science, Cochrane Library, and Age Line. Articles were selected according to the following criteria: (1) population: individuals defined as frail, prefrail, or transitioning to frail, and (2) outcome measures: quantitative gait variables as obtained by biomechanical analysis. Effect sizes (d) were calculated for the ability of parameters to discriminate between different frailty status groups.

RESULTS

Eleven publications met inclusion criteria. Frailty definitions, gait protocols and parameters were inconsistent, which made comparison of outcomes difficult. Effect sizes were calculated only for the three studies which compared at least two different frailty status groups. Gait speed shows the highest effect size to discriminate between frailty subgroups, in particular during habitual walking (d = 0.76-6.17). Gait variability also discriminates between different frailty status groups in particular during fast walking. Prominent parameters related to prefrailty are reduced cadence (d = 1.43) and increased step width variability (d = 0.64), whereas frailty (vs. prefrail status) is characterized by reduced step length during habitual walking (d = 1.32) and increased double support during fast walking (d = 0.78). Interestingly, one study suggested that dual-task walking speed can be used to predict prospective frailty development.

CONCLUSION

Gait characteristics in people with frailty are insufficiently analyzed in the literature and represent a major area for innovation. Despite the paucity of work, current results suggest that parameters beyond speed could be helpful in identifying different categories of frailty. Increased gait variability might reflect a multisystem reduction and may be useful in identifying frailty. In addition, a demanding task such as fast walking or adding a cognitive distractor might enhance the sensitivity and specificity of frailty risk prediction and classification, and is recommended for frailty assessment using gait analysis.

Kinetic Gait Analysis Using a Low-Cost Insole

Abnormal gait caused by stroke or other pathological reasons can greatly impact the life of an individual. Being able to measure and analyze that gait is often critical for rehabilitation. Motion analysis labs and many current methods of gait analysis are expensive and inaccessible to most individuals. The low-cost, wearable, and wireless insole-based gait analysis system in this study provides kinetic measurements of gait by using low-cost force sensitive resistors. This paper describes the design and fabrication of the insole and its evaluation in six control subjects and four hemiplegic stroke subjects. Subject-specific linear regression models were used to determine ground reaction force plus moments corresponding to ankle dorsiflexion/plantarflexion, knee flexion/extension, and knee abduction/adduction. Comparison with data simultaneously collected from a clinical motion analysis laboratory demonstrated that the insole results for ground reaction force and ankle moment were highly correlated (all >0.95) for all subjects, while the two knee moments were less strongly correlated (generally >0.80). This provides a means of cost-effective and efficient healthcare delivery of mobile gait analysis that can be used anywhere from large clinics to an individual's home.

Plantar Temperature Response to Walking in Diabetes with and without Acute Charcot: The Charcot Activity Response Test

Objective. Asymmetric plantar temperature differences secondary to inflammation is a hallmark for the diagnosis and treatment response of Charcot foot syndrome. However, little attention has been given to temperature response to activity. We examined dynamic changes in plantar temperature (PT) as a function of graduated walking activity to quantify thermal responses during the first 200 steps. Methods. Fifteen individuals with Acute Charcot neuroarthropathy (CN) and 17 non-CN participants with type 2 diabetes and peripheral neuropathy were recruited. All participants walked for two predefined paths of 50 and 150 steps. A thermal image was acquired at baseline after acclimatization and immediately after each walking trial. The PT response as a function of number of steps was examined using a validated wearable sensor technology. The hot spot temperature was identified by the 95th percentile of measured temperature at each anatomical region (hind/mid/forefoot). Results. During initial activity, the PT was reduced in all participants, but the temperature drop for the nonaffected foot was 1.9 times greater than the affected side in CN group (P = 0.04). Interestingly, the PT in CN was sharply increased after 50 steps for both feet, while no difference was observed in non-CN between 50 and 200 steps. Conclusions. The variability in thermal response to the graduated walking activity between Charcot and non-Charcot feet warrants future investigation to provide further insight into the correlation between thermal response and ulcer/Charcot development. This stress test may be helpful to differentiate CN and its response to treatment earlier in its course.

Virtualizing the assessment: a novel pragmatic paradigm to evaluate lower extremity joint perception in diabetes

BACKGROUND

Individuals with diabetes have a higher risk of falls and fall-related injuries. People with diabetes often develop peripheral neuropathy (DPN) as well as nerve damage throughout the body. In particular, reduced lower extremity proprioception due to DPN may cause a misjudgment of foot position and thus increase the risk of fall.

OBJECTIVE

An innovative virtual obstacle-crossing paradigm using wearable sensors was developed in an attempt to assess lower extremity position perception damage due to DPN.

METHODS

67 participants (age 55.4 ± 8.9, BMI 28.1 ± 5.8) including diabetics with and without DPN as well as aged-matched healthy controls were recruited. Severity of neuropathy was quantified using a vibratory perception threshold (VPT) test. The ability of perception of lower extremity was quantified by measuring obstacle-crossing success rate (OCSR), toe-obstacle clearance (TOC), and reaction time (T(R)) while crossing a series of virtual obstacles with heights at 10% and 20% of the subject's leg length.

RESULTS

No significant difference was found between groups for age and BMI. The data revealed that DPN subjects had a significantly lower OCSR compared to diabetics with no neuropathy and controls at an obstacle size of 10% of leg length (p < 0.05). DPN subjects also demonstrated longer T(R) compared to other groups and for both obstacle sizes. In addition, TOC was reduced in neuropathy groups. Interestingly, a significant correlation between T(R) and VPT (r = 0.5, p < 10(-3)) was observed indicating a delay in reaction with increasing neuropathy severity. The delay becomes more pronounced by increasing the size of the obstacle. Using a regression model suggests that the change in T(R) between obstacle sizes of 10% and 20% of leg length is the most sensitive predictor for neuropathy severity with an odds ratio of 2.70 (p = 0.02).

CONCLUSION

The findings demonstrate proof of a concept of virtual-reality application as a promising method for objective assessment of neuropathy severity, however a further study is warranted to establish a stronger relationship between the measured parameters and neuropathy.