Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults

Absolute and Relative Reliability of Spatiotemporal Gait Characteristics Extracted from an Inertial Measurement Unit among Senior Adults Using a Passive Hip Exoskeleton: A Test-Retest Study

BACKGROUND

Seniors wearing a passive hip exoskeleton (Exo) show increased walking speed and step length but reduced cadence. We assessed the test-retest reliability of seniors' gait characteristics with Exo.

METHODS

Twenty seniors walked with and without Exo (noExo) on a 10 m indoor track over two sessions separated by one week. Speed, step length, cadence and step time variability were extracted from one inertial measurement unit (IMU) placed over the L5 vertebra. Relative and absolute reliability were assessed using the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and minimal detectable change (MDC).

RESULTS

The relative reliability of speed, step length, cadence and step time variability ranged from "almost perfect to substantial" for Exo and noExo with ICC values between 0.75 and 0.87 and 0.60 and 0.92, respectively. The SEM and MDC values for speed, step length cadence and step time variability during Exo and noExo were <0.002 and <0.006 m/s, <0.002 and <0.005 m, <0.30 and <0.83 steps/min and <0.38 s and <1.06 s, respectively.

CONCLUSIONS

The high test-retest reliability of speed, step length and cadence estimated from IMU suggest a robust extraction of spatiotemporal gait characteristics during exoskeleton use. These findings indicate that IMUs can be used to assess the effects of wearing an exoskeleton on seniors, thus offering the possibility of conducting longitudinal studies.

The correlation of gait and muscle activation characteristics with locomotion dysfunction grade in elderly individuals

Objective

To investigate the differences and regularity of gait and muscle activation characteristics parameters in the Locomotion Dysfunction Grade (LDG) scale assessment in elderly individuals, and analyse the correlation between objective parameters and scale grading. Thus, to propose a novel detection mode for elderly individuals, which combined the LDG scale with objective detection. It can not only provide quantitative data for intelligent evaluation and rehabilitation, but also provided more accurate reference for the classification of care levels in elderly care policies.

Methods

Elderly individuals (n = 159) who underwent gait analysis and sEMG at the Chinese Rehabilitation Research Center from January 2019 to September 2023 were included. According to the LDG scale, the elderly individuals were divided into four groups, namely, the LDG4, LDG5, LDG6 groups and the healthy control group. Four indicators, namely, spatiotemporal, kinematic, dynamic gait parameters and muscle activation characteristics data, were collected. Changes in these characteristics of elderly individuals with lower extremity motor dysfunction were evaluated and analysed statistically.

Results

The spatiotemporal gait parameters were significantly lower in the LDG4, LDG5, LDG6 groups than in the healthy control group. The double support phase was positively correlated with the LDG, while the swing phase, step length and velocity were negatively correlated (P < 0.05). The movement angles of both hips, knees and ankles were significantly limited and negatively correlated with the LDG (P < 0.05). Compared with those in the healthy control group, the centre of pressure (COP) path length were greater, and the average COP velocity was significantly lower (P < 0.05) in the LDG4, LDG5, LDG6 groups. The regularity of muscle activation clearly changed. The root mean square of the gastrocnemius medialis was positively correlated with LDG (P < 0.05), while the tibialis anterior showed no regularity.

Conclusion

As the LDG increased, the differences in spatiotemporal, kinematic and dynamic gait parameters between elderly individuals with motor dysfunction and the healthy individuals gradually increased. The muscle activation characteristics parameters showed an abnormal activation pattern. These parameters were correlated with the LDG, providing a more comprehensive and objective assessment of lower extremity motor function in elderly individuals, improve assessment accuracy, and help accurate rehabilitation.

The Agreement between Wearable Sensors and Force Plates for the Analysis of Stride Time Variability

The variability and regularity of stride time may help identify individuals at a greater risk of injury during military load carriage. Wearable sensors could provide a cost-effective, portable solution for recording these measures, but establishing their validity is necessary. This study aimed to determine the agreement of several measures of stride time variability across five wearable sensors (Opal APDM, Vicon Blue Trident, Axivity, Plantiga, Xsens DOT) and force plates during military load carriage. Nineteen Australian Army trainee soldiers (age: 24.8 ± 5.3 years, height: 1.77 ± 0.09 m, body mass: 79.5 ± 15.2 kg, service: 1.7 ± 1.7 years) completed three 12-min walking trials on an instrumented treadmill at 5.5 km/h, carrying 23 kg of an external load. Simultaneously, 512 stride time intervals were identified from treadmill-embedded force plates and each sensor where linear (standard deviation and coefficient of variation) and non-linear (detrended fluctuation analysis and sample entropy) measures were obtained. Sensor and force plate agreement was evaluated using Pearson's r and intraclass correlation coefficients. All sensors had at least moderate agreement (ICC > 0.5) and a strong positive correlation (r > 0.5). These results suggest wearable devices could be employed to quantify linear and non-linear measures of stride time variability during military load carriage.

Laboratory-assessed gait cycle entropy for classifying walking limitations among community-dwelling older adults

Among older people, walking difficulty results from actual and perceived declines in physical capacities and environmental requirements for walking. We investigated whether the physiological complexity of the gait cycle covaries with experience of walking difficulty. Walking difficulty, gait speed, and gait cycle complexity were evaluated among 702 community-dwelling older people aged 75, 80, and 85 years who took part in the six-minute walking test in the research laboratory. Walking difficulty for 500 m was self-reported. Complexity was quantified as trunk acceleration multiscale entropy during the gait cycle. Complexity was then compared between those with no reported walking difficulty, walking with modifications but no difficulty, and those reporting walking difficulty. Higher entropy differentiated those reporting no difficulty walking from those reporting walking difficulties, while those reporting having modified their walking, but no difficulty formed an intermediate group that could not be clearly distinguished from the other categories. The higher complexity of the gait cycle is associated with slower gait speed and the presence of self-reported walking difficulty. Among older people, gait cycle complexity which primarily reflects the biomechanical dimensions of gait quality, could be a clinically meaningful measure reflecting specific features of the progression of walking decline. This encourages further investigation of the sensitivity of gait cycle complexity to detect early signs of gait deterioration and to support targeted interventions among older people.

The gait is less stable in children with cerebral palsy in normal and dual-task gait compared to typically developed peers

There is limited evidence about gait stability and its alteration by concurrent motor and cognitive tasks in children with cerebral palsy (CP). We examined gait stability and how it is altered by constrained cognitive or motor task in CP and their typically developed (TD) controls. Gait kinematics were recorded using inertial-measurement units (IMU) from 18 patients with hemiplegia (13.5 ± 2.4 years), 12 with diplegia (13.0 ± 2.1 years), and 31 TD controls (13.5 ± 2.2 years) during unconstrained gait, and motor (carrying a tray) and cognitive (word naming) task constrained gait at preferred speed (~400 steps/task). Step duration, its standard deviation and refined-compound-multiscale entropy (RCME) were computed independently for vertical and resultant horizontal accelerations. Gait complexity was higher for patients with CP than TD in all tasks and directions (p < 0.001-0.01), being pronounced in vertical direction, cognitive task and for diplegic patients (p < 0.05-0.001). The gait complexity increased more (i.e. higher dual-task cost) from the unconstrained to the constrained gait in CP compared to TD (p < 0.05). Step duration was similar in all groups (p > 0.586), but its variation was higher in CP than TD (p < 0.001-0.05), and during the constrained than unconstrained gait in all groups (p < 0.01-0.001). The gait in children with CP was more complex and the dual-task cost was higher primarily for children with diplegic CP than TD during cognitive task, indicating that attentional load hinders their gait more. This raises the hypothesis that more attention and cortical resources are needed to compensate for the impaired gait in children with CP.

Indirect Recognition of Predefined Human Activities

The work investigates the application of artificial neural networks and logistic regression for the recognition of activities performed by room occupants. KNX (Konnex) standard-based devices were selected for smart home automation and data collection. The obtained data from these devices (Humidity, CO₂, temperature) were used in combination with two wearable gadgets to classify specific activities performed by the room occupant. The obtained classifications can benefit the occupant by monitoring the wellbeing of elderly residents and providing optimal air quality and temperature by utilizing heating, ventilation, and air conditioning control. The obtained results yield accurate classification.