Feature extraction from ear-worn sensor data for gait analysis

This scoping review aimed to gather current knowledge on accurately identifying and distinguishing between non-frail, pre-frail, and frail older adults using gait and daily physical activity (DPA) parameters and/or models that combine gait with DPA parameters in both controlled and daily life environments. Following PRISMA-ScR guidelines, a systematic search was conducted across seven databases using key terms: "frail", "gait or walk", "IMU", and "age". Studies were included if they focused on gait analysis using Inertial Measurement Units (IMUs) for walking distances greater than 10 meters. Extracted data included study design, gait and DPA outcomes, walking conditions, and classification model performance. Gait parameters were grouped into four domains: spatio-temporal, frequency, amplitude, and dynamic gait. DPA parameters were synthesized into three categories: postural and transition, variability, and physical activity pattern. A total of 15 cross-sectional studies involving 2,366 participants met the inclusion criteria. Gait analysis showed (pre)frail individuals had slower, shorter steps with longer stride times compared to non-frail individuals. Pre-frail individuals showed distinct gait patterns in periodicity, magnitude range, and variability. In daily activities, (pre)frail individuals displayed shorter, fragmented walking periods and longer transitions between positions. Walking variation identified pre-frail status, showing progressive decreases from non-frail to frail states. Combined gait and daily physical activity models achieved over 97% accuracy, sensitivity and specificity in distinguishing between groups. This review provides an updated synthesis of the relationship between various gait and/or DPA parameters and physical frailty, highlighting gaps in pre-frailty detection and the variability in measurement protocols. It underscores the potential of long-term, sensor-based monitoring of daily physical activity for advancing pre-frailty screening and guiding future clinical trials. Structured Abstract BACKGROUND: Changes in gait and physical activity are critical indicators of frailty. With advancements in wearable sensor technology, long-term gait analysis using acceleration data has become more feasible. However, the contribution of parameters beyond gait speed, such as gait dynamics and daily physical activity (DPA), in identifying frail and pre-frail individuals remains unclear. This scoping review aimed to gather knowledge on accurately identifying and differentiating physical pre-frail and frail individuals from non-frail individuals using gait parameters alone or models that combine gait and DPA parameters, both in controlled settings and daily life environments. The review followed PRISMA-ScR guidelines. A search strategy incorporating key terms-"frail", "gait or walk", "IMU", and "age"-was applied across seven databases from inception to March 1, 2024. Studies were included if they focused on gait analysis in controlled or daily environments using Inertial Measurement Units (IMUs) and involved walking distances longer than 10 meters. Data on walking conditions, gait outcomes, classification methods, and results were extracted. Gait parameters were categorized into four domains: spatio-temporal, frequency, amplitude, and dynamic gait. DPA parameters were synthesized into three categories: postural and transition, variability, physical activity pattern. A total of 15 cross-sectional observational studies met the eligibility criteria, covering 2,366 participants, with females representing 27%-80% of the sample and ages ranging from 60 to 92 years. Regarding gait parameters, (pre)frail individuals exhibited longer stride times, slower walking speeds, shorter steps, and reduced cadence compared to non-frail individuals. In three studies, pre-frail could be distinguished from the non-frail and frail group through gait periodicity, range of magnitude, and gait variability. DPA patterns differed between groups, with (pre)frail individuals showing shorter and more fragmented walking periods, brief walking bouts and longer postural transitions. Walking bout variation (CoV) effectively identified pre-frail status, decreasing 53.73% from non-frail to pre-frail, and another 30.87% from pre-frail to frail. Models combining both gait and DPA parameters achieved the highest accuracy (97.25%), sensitivity (98.25%), and specificity (98.25%) in distinguishing between groups. This scoping review provides an updated overview of the current knowledge and gaps in understanding the relationship between gait parameters across different domains and DPA parameters along with physical frailty. Significant variability in gait measurement methods and protocols complicates direct comparisons between studies. The review emphasizes the need for further research, particularly in pre-frailty screening, and underscores the potential of inertial sensor-based long-term monitoring of daily physical activity for future clinical trials.

Sporadic (SSP) and hereditary spastic paraplegias (HSP) are clinically and genetically heterogeneous disorders, which are characterised by a slowly progressive spastic paraparesis. Initial symptoms and the rate of progression are variable even among members of the same family. Spastic paraparesis is the major and most disabling clinical symptom and was assessed with gait analysis using a three-dimensional infrared movement analysis system. 22 patients with clinically and/or genetically confirmed SSP/HSP were compared with age-matched control subjects. Significantly lower values were found for gait velocity, stride length, step height and the range of motion of the knee-angle. The gait pattern is characterised by a severe spasticity of both legs with only mild paresis. The balance-related gait parameters show a broad-based gait without inwardly rotated feet. No correlation was found between disease duration and the severity of the gait disorder and the central motor conduction time to the leg muscles and the abnormal gait parameters. The gait pattern did not differ between the 7 SSP cases and the 15 HSP cases. We conclude that three-dimensional gait analysis can uncover specific features of such rare gait disorders, and may be used as an objective tool to quantify the impairment of gait parameters in patients with SSP/HSP and thus can be used to monitor disease progression and the effect of therapeutic interventions.

Background and objectives: Objective, accurate, and intuitive evaluation of knee joint function in patients with knee osteoarthritis (KOA) is important. This study aimed to clarify the gait characteristics of patients with bilateral KOA and their correlation with Western Ontario and McMaster University Osteoarthritis Index (WOMAC). Materials and Methods: 20 patients with bilateral KOA and 20 conditionally matched healthy individuals were enrolled in the experimental and control groups, respectively. Footscan and CODA motion gait analysis systems were used to analyse the gait parameters. Gait spatiotemporal parameters and knee joint motion parameters were collected. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Patients in the experimental group were evaluated using WOMAC. Pearson’s correlation analysis was performed on the gait data and WOMAC score data of the experimental group. Results: Velocity, cadence, step length, and stride length of the experimental group were significantly lower than those of the control group (p < 0.01). Step time and gait cycle were significantly greater in the experimental group than in the control group (p < 0.01). Total stance and double-stance times of the experimental group were significantly greater than those of the control group (p < 0.01), whereas the single-stance time was shorter than that of the control group (p < 0.01). The range of motion and maximum flexion angle in the experimental group were significantly lower than those in the control group (p < 0.01), and the minimum angle of knee extension was greater than that in the control group (p < 0.01). The discrete trend of weight-bearing balance and walking stability gait index in the experimental group was greater than that in the control group. The WOMAC score and gait analysis were significantly correlated (p < 0.05). Conclusions: The gait function of patients with KOA is significantly worse than that of normal people. The WOMAC scale and gait analysis can be used to assess KOA severity from different perspectives with good consistency.

Gait analysis systems are essential for rehabilitation but are often time-consuming and less accessible in low- and middle-income countries. GAITWell was developed to address these challenges with its portable and modular design for automated gait data collection and analysis. This study evaluates its methodological properties. GAITWell uses discrete binary sensors on interconnected plates to capture gait data, analyzed using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, which identifies key reference points like foot contact and toe-off. DBSCAN detects clusters of arbitrary shapes and sizes, separates noise from data, and identifies natural patterns within the data space without prior group knowledge. Each plate measures 44 cm × 37 cm and has an 11 × 7 sensor array with 4 cm spacing. Test–retest reliability was evaluated using the intraclass correlation coefficient (ICC), standard error of the mean (SEM), and Bland–Altman plots. Concurrent validity was assessed by comparing GAITWell measurements to those from the Qualisys Pro-Reflex system. Results: 38 healthy adults participated (average age 33.2 years, SD 13.0). Correlations between GAITWell and Qualisys ranged from moderate (right step length) to very high (gait speed, cycle time, right and left step time, left step length, stance time, swing time, right and left cadence, and base of support). Moderate to good agreement was found for gait speed, cycle time, stride length, right and left step length, right and left step time, and stance and swing time, but poor agreement was observed for double support times, right and left cadence, and base of support. Preliminary analysis suggests that increasing sensor resolution could reduce measurement error by 70%. Conclusions: GAITWell is a promising tool, with future research focusing on enhancing sensor accuracy for improved reliability.

The effects of different carrying methods on human gait parameters

Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation () with the gold standards across all assessed gait parameters except for cycle time (). Similarly, the coefficient of determination was high () for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity (). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments.

Gait pattern alteration by functional sensory substitution in healthy subjects and in diabetic subjects with peripheral neuropathy

Category: Ankle Arthritis Introduction/Purpose: Ankle arthrodesis is still the primary treatment for end-stage arthritis of the ankle that does not respond to conservative treatment. However, comparative studies demonstrated that the patients’ functional outcomes remain significantly lower than normal, progression of subtalar and midfoot arthritis and there could be measurable abnormalities in their gait parameters. Previous studies demonstrated gait analysis after ankle arthrodesis using 3D motion capture system. These studies used a single segment foot model, which had the limitation of detailed motion analysis. 3D multi-segmental foot model enables to perform detailed analysis segmentally such as fore foot and hind foot. The purpose of this study was to examine foot kinematics during walking after ankle arthrodesis using 3D multi-segment foot model as compared with a healthy control group. Methods: Between 2014 and 2016, nine patients who underwent an isolated ankle arthrodesis were followed for a mean 2 years after surgery, and five control subjects were included for comparison. Physical examination, radiographic examination and gait examination were performed. For gait analysis Vicon Nexus system with 16 MX-Cameras was used to capture foot kinematics during barefoot walking at self-selected speed along a 10 m walkway. Markers were placed according to the Oxford Foot Model (OFM). Patients completed preoperative and annual postoperative functional outcome scores including the Japanese Society for Surgery of the Foot (JSSF) scale. Results: JSSF scale was significantly improved from pre-operation to post-operation (50 points versus 85 points; p&lt;0.05). The range of sagittal motion in hind foot during one gait cycle was significantly smaller in the arthrodesis group than in the healthy group (4.6 degrees versus 20 degrees; p&lt;0.05). The range of coronal motion in hind foot was also significantly smaller in the arthrodesis group than that in the healthy group (3.7 degrees versus 15.1 degrees; p&lt;0.05). There was no significant difference in the range of sagittal motion in forefoot between arthrodesis group and healthy group (20.2 degrees versus 16.6 degrees). However, there were significant differences at heel contact. Forefoot in arthrodesis group was significantly toward plantarflexion (6.1 degrees versus -2.0 degrees; p&lt;0.05). Conclusion: In this study, detailed motion of foot after ankle arthrodesis could be analyzed by using OFM. Range of sagittal motion in hind foot in arthrodesis group during one gait cycle was significantly smaller than that in healthy group. However, no significant difference was observed in the forefoot. The same result was also obtained on the frontal plane. In arthrodesis group, forefoot tended to be more plantarflexion than healthy group in gait, especially there was significant difference at heel contact. These findings suggested to cause lower functional outcomes and the progression of subtalar and midfoot arthritis after ankle arthrodesis.

BackgroundThe step-by-step determination of the spatio-temporal parameters of gait is clinically relevant since it provides an estimation of the variability of specific gait patterns associated with frequent geriatric syndromes. In recent years, several methods, based on the use of magneto-inertial units (MIMUs), have been developed for the step-by-step estimation of the gait temporal parameters. However, most of them were applied to the gait of healthy subjects and/or of a single pathologic population. Moreover, spatial parameters in pathologic populations have been rarely estimated step-by-step using MIMUs. The validity of clinically suitable MIMU-based methods for the estimation of spatio-temporal parameters is therefore still an open issue. The aim of this study was to propose and validate a method for the determination of both temporal and spatial parameters that could be applied to normal and heavily compromised gait patterns.MethodsTwo MIMUs were attached above each subject’s ankles. An instrumented gait mat was used as gold standard. Gait data were acquired from ten hemiparetic subjects, ten choreic subjects, ten subjects with Parkinson’s disease and ten healthy older adults walking at two different gait speeds. The method detects gait events (GEs) taking advantage of the cyclic nature of gait and exploiting some lower limb invariant kinematic characteristics. A combination of a MIMU axes realignment along the direction of progression and of an optimally filtered direct and reverse integration is used to determine the stride length.ResultsOver the 4,514 gait cycles analyzed, neither missed nor extra GEs were generated. The errors in identifying both initial and final contact at comfortable speed ranged between 0 and 11 ms for the different groups analyzed. The stride length was estimated for all subjects with less than 3% error.ConclusionsThe proposed method is apparently extremely robust since gait speed did not substantially affect its performance and both missed and extra GEs were avoided. The spatio-temporal parameters estimates showed smaller errors than those reported in previous studies and a similar level of precision and accuracy for both healthy and pathologic gait patterns. The combination of robustness, precision and accuracy suggests that the proposed method is suitable for routine clinical use.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-152) contains supplementary material, which is available to authorized users.

Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is essential for the individualized treatment of motor disorders such as cerebral palsy (CP). The primary contribution of this study is the introduction of a multimodal fuzzy logic system-based gait index (FLS-GIS), designed to provide numerical scores for gait patterns in both healthy children and those with CP, before and after surgery. This study examines and evaluates the surgical outcomes in children with CP who have undergone Achilles tendon lengthening. The FLS-GIS utilizes hierarchical feature fusion and fuzzy logic models to systematically evaluate and score gait patterns, focusing on spatial and temporal features across the hip, knee, and ankle joints. The two FLS types-1 (FLS-GIS-T1) and type-2 (FLS-GIS-T2) indices, respectively, were implemented to comprehensively study gait profiles. Starting with the gait parameters of all subjects, the changes in gait parameters in post-surgery children reflect significant improvements in gait dynamics, bringing walking patterns in CP children closer to those of their typically healthy peers. Both FLS-GIS-T1 and FLS-GIS-T2 demonstrated significant improvements in post-surgery evaluations compared to pre-surgery assessments, with p values < 0.05 and < 0.001, respectively, when compared to traditional indices. The proposed FLS-based index offers clinicians a robust and standardized gait evaluation tool, characterized by a fixed range of values, enabling consistent assessment across various gait conditions.

In this paper, we describe the design procedure of an above-knee powered prosthetic leg and an algorithm to generate appropriate gait patterns that are synchronized with the movement of the user. The developed prosthetic leg has powered knee and ankle joints for transfemoral amputees, and its weight and dimensions were determined on the basis of human body data. In particular, two degrees of freedom (roll and pitch axes) were adopted in the ankle joint to achieve dynamic balance control on uneven ground, and passive toe joints using a crank-rocker mechanism and torsional springs were attached at the foot to increase the walking stability. In addition, we developed a walking pattern simulator that is able to test the walking patterns of the powered prosthetic leg in the air. By attaching two inertial sensors on both thighs of the user and measuring both thigh motions, the per cent of gait cycle is suitably calculated from the proposed algorithm, and smooth gait motions are generated according to the gait cycle percent. Finally, walking patterns of the powered prosthetic leg were successfully generated by synchronizing to the human gait, and the generated gaits were analyzed by comparing them to the human gait.

Parkinson's disease (PD) is a chronic condition that can be diagnosed and monitored by evaluating changes in the gait and arm movement parameters. In the gait movement, each cycle consists of two phases: stance and swing. Using gait analysis techniques, it is possible to get spatiotemporal variables derived from both phases. In this paper, we compared two techniques: wavelet and peak detection. Previously, the wavelet technique was assessed for the gait phases detection, and peak detection was evaluated for arm swing analysis. These methods were evaluated using a low-cost RGB-D camera as data input source. This comparison could provide a unified and integrated method to analyze gait and arm swing signals. Twenty-five PD patients and 25 age-matched, healthy subjects were included. Mann-Whitney U test was used to compare the continuous variables between groups. Hamming distances and Spearman rank correlation were used to evaluate the agreement between the signals and the spatiotemporal variables obtained by both methods. PD group showed significant reductions in speed (wavelet p = 0.001, peak detection p <0.001) and significantly greater swing (wavelet p = 0.003, peak detection p =0.005) and stance times (wavelet p = 0.003, peak detection p =0.004). Hamming distances showed small differences between the signals obtained by both methods (16 to 18 signal points). A very strong correlation (Spearman rho > 0.8, p <0.05) was found between the spatiotemporal variables obtained by each signal processing technique. Wavelet and peak detection techniques showed a high agreement in the signal obtained from gait data. The spatiotemporal variables obtained by both methods showed significant differences between the walking patterns of PD patients and healthy subjects. The peak detection technique can be used for integral motion analysis, providing the identification of the phases in the gait cycle, and arm swing parameters.Clinical Relevance- this establishes that peaks and wavelet techniques are comparable and may use it interchangeably to process signals from the gait of Parkinson's disease patients to support diagnosis and follow up made by a clinical expert.

Limb salvage surgery (LSS) with megaprosthesis is a common treatment for distal femur tumors, but its impact on gait remains poorly understood. Traditional gait analysis methods are costly and require specialized equipment. This study aims to compare spatiotemporal gait parameters between patients with distal femur megaprosthesis and healthy controls using an inertial measurement unit (IMU). We conducted a case-control study with 79 participants: 31 patients with distal femur megaprosthesis and 48 healthy controls. Gait data were collected using an IMU placed at L5-S1, capturing metrics such as gait quality index (GQI), pelvic kinematics, propulsion index, and gait speed. Statistical analysis included Student's t-test, Mann-Whitney U test, and one-way ANOVA to compare gait parameters across groups. Patients with megaprosthesis exhibited significantly lower gait speed, propulsion index and anteroposterior acceleration symmetry index compared to controls (p<.05). GQI was reduced in the healthy legs of the cases (92.3%) compared to control legs (96.6%). Adaptations included prolonged stance phases in healthy legs and decreased single support phases in prosthetic legs. Despite these changes, gait patterns remained within functional ranges. IMU-based gait analysis reveals significant but functional alterations in gait mechanics among patients with distal femoral megaprosthesis. These findings underscore the need for tailored rehabilitation strategies to address compensatory mechanisms, optimize mobility, and enhance long-term outcomes. The use of IMU technology offers a cost-effective and portable alternative for clinical gait assessments.

Selection of broiler strains for high body weight has changed the anatomical characteristics and in connection to that, the pattern of locomotion. In addition, rapid growing broilers show a high incidence of leg disorders which compromise the walking ability of the birds. Differences in the patterns of locomotion between laying hens and broilers and between broilers with and without leg disorders can be demonstrated and quantified by gait analysis. The gait pattern was recorded by videotracking. Three points of the body - the cloacal region and both feet joints - were marked by small patches of reflecting foils. The vertical and horizontal movements of the marked points were recorded by a camera in posterior position, while the bird was walking on a treadmill The camera was connected with a PC-operated videotracking system. The vertical and horizontal movements of the 3 marked points were recorded simultaneously and plotted against the time axis. Kinetograms show clearly the differences in the walking pattern between broilers and layers. Layers place the legs directly under the centre of gravity and, therefore, the body moves in a straight line. Broilers, in contrast, move the centre of gravity step by step laterally towards the position of the supporting leg. This pattern may be caused by the anatomical characteristics of broilers. Limping in broilers with leg problems can be measured by differences in the lateral and vertical movements of the right and left leg.

Purpose This study was designed to examine the effects of a single corrective exercise (CEX) and corrective kinesio taping (CKT) on gait patterns, plantar pressure, balance, and pain in 20~30s female patients with moderate hallux valgus. Methods Twenty-one participants (age: 30.1±5.1 yrs; height: 164.1±4.8 cm; body weight: 56.7±6.8 kg; body mass index: 21.2±5.7 kg·m-2; hallux valgus angle: 27.2±6.1°) with hallux valgus was recruited and participated in three trials, i.e., CEX trial, CKT trial, and combined CEX and CKT (CEX+CKT) trial, repeatedly in a counter-balanced order. One week of wash-out period was placed between the trials to minimize the effect of the previous treatment on the next treatment. Variables related to gait pattern, plantar pressure, balance, and pain were measured during each treatment. We carried out repeated two way ANOVA on measured variables. Results 1) Regarding gait patterns, CEX treatment and CEX+CKT treatments showed significant increases in the length of patients strides, the single support line during the stance phase, and significant reduction of the cadence. 2) Regarding gait cycle, CEX treatment and CEX+CKT treatments showed significant reductions in the contact times of forefoot, midfoot, and heel. There was a significant reduction of double stance phase in CEX treatment. 3) Regarding foot pressure on gait, CEX+CKT treatments significantly increased the maximum pressure of midfoot and heel. CEX treatments significantly increased the maximum pressure of forefoot. 4) Regarding balance, CEX treatment and CKT treatments significantly increased one leg standing with eyes closed. 5) Pain was significantly reduced in CKT treatment and CEX+CKT treatments. Conclusions According to the aforementioned results, it was concluded that a single CKT treatment was effective in reducing pain when walking and that plantar pressure, gait pattern, gait cycle, and balance were improved through a single bout of CEX treatments. Therefore, treatments by stage, starting with CKT treatments to reduce the pain, and then treating CEX to improve the gait pattern, gait cycle, foot pressure when walking, and balance ability, would be effective. Future research is warranted to identify the effects of long-term treatments.