Search Results (58)

Background: With increasing pharmacokinetic evidence suggesting the inadequacy of conventional dose intravenous co-amoxiclav (IVCA) 1.2 g Q8H in targeting Enterobacterales, our institution antibiotic guidelines optimised dosing recommendations for diabetic foot infection (DFI) management to 1.2 g Q6H in August 2023. In this study, we aim to evaluate the efficacy and safety of the optimised dose IVCA in DFI treatment. Methods: In this single-centre cohort study, patients ≥ 21 years with DFI, creatinine clearance ≥ 50 mL/min, and weight > 50 kg, who were prescribed IVCA 1.2 g Q8H (standard group (SG)), were compared with those prescribed IVCA 1.2 g Q6H (optimised group (OG)). Patients who were pregnant, immunocompromised, had nosocomial exposure in last 3 months, or received < 72 h of IVCA were excluded. The primary efficacy outcome was clinical deterioration at end of IVCA monotherapy. The secondary efficacy outcomes include 30-day readmission and mortality, empiric escalation of antibiotics, lower limb amputation, and length of hospitalisation. The safety outcomes include hepatotoxicity, renal toxicity, and diarrhoea. Results: There were 189 patients (94 in SG; 95 in OG) included. Patients in SG (31.9%) were twice as likely to experience clinical deterioration compared to OG (16.8%) (odds ratio: 2.31, 95% confidence interval: 1.16–4.62, p < 0.05). There were statistically more patients who had 30-day all-cause mortality in SG (5.3%) compared to OG (0%) (p < 0.05). Furthermore, 30-day readmission due to DFI in SG (26.6%) was higher compared to OG (11.6%) (p < 0.05). Empiric escalation of IV antibiotics was required for 14.9% patients in SG and 6.3% patients in OG (p = 0.06). There was no statistical difference for lower limb amputation (p = 0.72), length of hospitalisation (p = 0.13), and the occurrence of safety outcomes in both groups. Conclusions: This study suggests IVCA 1.2 g Q6H is associated with the decreased likelihood of clinical deterioration and is likely as safe as IVCA 1.2 g Q8H. The optimised dose of IVCA may help reduce the use of broad-spectrum antibiotics due to clinical deterioration. Full article

Background/Objectives: This study focuses on the motion planning and control of an active ankle–foot orthosis (AFO) that leverages biomechanical insights to mitigate footdrop, a deficit that prevents safe toe clearance during walking. Methods: To adapt the motion of the device to the user’s walking speed, a geometric model was used, together with real-time measurement of the user’s gait cycle. A geometric speed-adaptive model also scales a trapezoidal ankle-velocity profile in real time using the detected gait cycle. The algorithm was tested at three different walking speeds, with a prototype of the AFO worn by a test subject. Results: At walking speeds of 0.44 and 0.61 m/s, reduced tibialis anterior (TA) muscle activity was confirmed by electromyography (EMG) signal measurement during the stance phase of assisted gait. When the AFO was in assistance mode after toe-off (initial and mid-swing phase), it provided an average of 48% of the estimated required power to make up for the deliberate inactivity of the TA muscle. Conclusions: Kinematic analysis of the motion capture data showed that sufficient foot clearance was achieved at all three speeds of the test. No adverse effects or discomfort were reported during the experiment. Future studies should examine the device in populations with footdrop and include a comprehensive evaluation of safety. Full article

Background: Among older adults, there is a high incidence of history of fall (HoF), fear of falling (FoF), and falls on stair descent during gait transitions. Purpose: We aim to evaluate the association between HoF and FoF on spatiotemporal and lower-limb kinematic parameters in older adults during stair descents and gait transitions. Methods: Sixty older adults (>60 years) were evaluated through an optoelectrical motion capture system during stair descents and gait transitions, using the mean value of the task velocity and time; single- and double-support time; peak downward center of mass (CoM) velocity; hip, knee, and ankle positions of ipsi and the contralateral limb; and foot clearance and foot placement, assessed through multivariate analysis of variance. Results: FOF exhibited longer time to complete (p = 0.009) and double-support (p = 0.047) and single-support (p = 0.009) times and a reduced peak downward CoM velocity (p = 0.043). In the gait transition cycle, HOF exhibited reduced ipsi ankle angles at toe-off (p = 0.015), and FOF presented reduced ipsi ankle angles at heel-strike (p = 0.041) and toe-off (p = 0.026) and reduced contralateral ankle angles at toe-off (p = 0.022). Conclusion: Older adults with HoF and FoF exhibit biomechanical changes during stair descents and gait transitions, in line with the use of more conservative strategies to avoid falling. Full article

Human gait motions differ depending on the age of the person. Previous studies have estimated age categories of walkers or have used age analysis for security or commercial surveillance purposes using images. However, few studies have estimated age from gait parameters alone. We estimated the age of people using kernel regression analysis based on their height, weight, and representative gait parameters, i.e., walking features that are interpretable with relative ease. Samples were obtained from 75 Japanese women aged 20–70 in a database. Through a variable selection based on sensitivity analysis, the established model estimated the ages of the women with a correlation coefficient of 0.78 with their actual ages, and the mean absolute error was 9.99 years. The sensitive variables included the minimum foot clearance, body weight, walking velocity, step width, and stride length. Estimation errors were significantly greater for elderly adults than for young people. Specifically, the mean absolute error for people in their 20s was $7.4$ years, whereas that for those over 60 was $13.1$ years. The proposed method uses gait parameters that can be measured with wearable devices, such as inertial measurement units; therefore, it offers an accessible approach to estimating a walker’s age with moderate certainty and promoting healthcare awareness in daily life. Full article

This study investigated the effects of ankle dorsiflexion angle adjustments in ankle–foot orthoses (AFOs) on the gait of healthy individuals. Fifteen healthy participants engaged in treadmill walking tasks while wearing AFOs with dorsiflexion angles set at 0°, 5°, 10°, and 15°. Three-dimensional treadmill gait analysis was used to collect data during treadmill walking. The analysis focused on toe clearance and the contribution of the vertical component of limb shortening (LS), and compared them across different dorsiflexion angles. The results indicated a significant increase in toe clearance at 10° (median [interquartile change]: 5.03 [0.90] vs. 5.98 [1.18], p < 0.01) and 15° (5.03 [0.90] vs. 5.82 [1.11], p < 0.01) dorsiflexion angle conditions compared to the 0° condition. Similarly, LS demonstrated significant increases at 10° (4.89 [1.97] vs. 5.87 [1.31], p < 0.01) and 15° (4.89 [1.97] vs. 5.61 [1.65], p < 0.01) conditions when compared with the 0° condition. These findings support the notion that higher dorsiflexion angles in AFOs lead to increased toe clearance and LS, suggesting the effectiveness of dorsiflexion angle adjustments as a strategy to address reduced toe clearance. Full article

Background: Advances in prosthetic technology, especially microprocessor-controlled knees (MPKs), have helped enhance gait symmetry and reduce fall risks for individuals who have undergone transfemoral amputation. However, challenges remain in walking in constrained situations due to the limitations of passive prosthetic feet, lacking ankle mobility. This study investigates the benefits of SYNSYS^®, a new microprocessor-controlled knee–ankle–foot system (MPKA_NEW), designed to synergize knee and ankle movements. Methods: A randomized crossover trial was conducted on 12 male participants who had undergone transfemoral amputation who tested both the MPKA_NEW and their usual MPK prosthesis. Biomechanical parameters were evaluated using quantitative gait analysis in various walking conditions. Participants also completed self-reported questionnaires on their quality of life, locomotor abilities, and prosthesis satisfaction. Results: The MPKA_NEW showed a significant reduction in the risk of slipping and tripping compared to standard MPK prostheses, as evidenced by increased flat-foot time and minimum toe clearance during gait analysis. The MPKA_NEW also improved physical component scores in quality-of-life assessments (Short-Form 36 General Health Questionnaire), suggesting enhanced stability and reduced cognitive load during walking. Conclusions: The MPKA_NEW offers significant improvements in gait safety and quality of life for people who have undergone TFA, particularly in challenging conditions. Further studies are needed to assess the long-term benefits and adaptability across diverse amputee populations. Full article

The continuous, automated monitoring of sensor-based data for walking capacity and mobility has expanded gait analysis applications beyond controlled laboratory settings to real-world, everyday environments facilitated by the development of portable, cost-efficient wearable sensors. In particular, the integration of Inertial Measurement Units (IMUs) into smart shoes has proven effective for capturing detailed foot movements and spatiotemporal gait characteristics. While IMUs enable accurate foot trajectory estimation through the double integration of acceleration data, challenges such as drift errors necessitate robust correction techniques to ensure reliable performance. This review analyzes current literature on shoe-based systems utilizing IMUs to estimate spatiotemporal gait parameters and foot trajectory characteristics, including foot–ground clearance. We explore the challenges and advancements in achieving accurate 3D foot trajectory estimation using IMUs in smart shoes and the application of advanced techniques like zero-velocity updates and error correction methods. These developments present significant opportunities for achieving reliable and efficient real-time gait assessment in everyday environments. Full article

Background: Overweight may present an additional challenge when crossing obstacles. More specifically it may affect adequate foot clearance to reduce the risk of obstacle contact. Thus, the objective of this study was to compare obstacle clearance and spatial–temporal gait parameters during obstacle crossing in young adults with normal body weight and overweight. Methods: Twenty-eight and fifteen individuals were categorized into normal body mass index (18.5–25 kg/m²) and overweight (25–30 kg/m²), respectively. The participants walked along a walkway at their preferred speed and stepped over an obstacle. Spatial–temporal parameters were calculated during the approaching (stride before obstacle) and the crossing (step over the obstacle) phases. Additionally, the leading and trailing foot placements prior to and after the obstacle and toe clearance were calculated. Results: No significant differences were found for the approach, the crossing phases and leading and trailing toe clearance. Analysis of foot placement distance prior to and after the obstacle showed that, compared to the individuals with normal body weight, overweight individuals significantly increased the leading foot placement distance prior to the obstacle (+7 cm, ↑ 6.7%) and increased the trailing foot placement distance after the obstacle (+8.1 cm, ↑ 9%). Conclusions: Our findings indicated that overweight individuals have a different obstacle crossing behavior regarding foot placement distance prior to and after the obstacle compared to normal-weight individuals without differences in spatial–temporal gait parameters or toe clearances. However, the results did not suggest that participants with overweight show a higher risk of tripping. Full article

Background/Objective: Muscle synergy analysis based on machine learning has significantly advanced our understanding of the mechanisms underlying the central nervous system motor control of gait and has identified abnormal gait synergies in stroke patients through various analytical approaches. However, discrepancies in experimental conditions and computational methods have limited the clinical application of these findings. This review seeks to integrate the results of existing studies on the features of muscle synergies in stroke-related gait abnormalities and provide clinical and research insights into gait rehabilitation. Methods: A systematic search of Web of Science, PubMed, and Scopus was conducted, yielding 10 full-text articles for inclusion. Results: By comprehensively reviewing the consistencies and differences in the study outcomes, we emphasize the need to segment the gait cycle into specific phases (e.g., weight acceptance, push-off, foot clearance, and leg deceleration) during the treatment process of gait rehabilitation and to develop rehabilitation protocols aimed at restoring normal synergy patterns in each gait phase and fractionating reduced synergies. Conclusions: Future research should focus on validating these protocols to improve clinical outcomes and introducing indicators to assess abnormalities in the temporal features of muscle synergies. Full article

Lower limb exoskeletons have been developed to improve functionality and assist with daily activities in various environments. Although these systems utilize sensors for gait phase detection, they lack anticipatory information about environmental changes, which limits their adaptability. This paper presents a vision-based intelligent gait environment detection algorithm for a lightweight ankle exosuit designed to enhance gait stability and safety for stroke patients, particularly during stair negotiation. The proposed system employs YOLOv8 for real-time environment classification, combined with a long short-term memory (LSTM) network for spatio-temporal feature extraction, enabling the precise detection of environmental transitions. An experimental study evaluated the classification algorithm and soft ankle exosuit performance through three conditions using kinematic analysis and muscle activation measurements. The algorithm achieved an overall accuracy of over 95% per class, which significantly enhanced the exosuit’s ability to detect environmental changes, and thereby improved its responsiveness to various conditions. Notably, the exosuit increased the ankle dorsiflexion angles and reduced the muscle activation during the stair ascent, which enhanced the foot clearance. The results of this study indicate that advanced spatio-temporal feature analysis and environment classification improve the exoskeleton’s gait assistance, improving adaptability in complex environments for stroke patients. Full article

Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems have been designed to monitor users’ gait patterns, they commonly spend a lot of time and effort to extract gait metrics from signal data. This study aims to design an artificial intelligence-empowered and economic-friendly gait monitoring system. A pair of intelligent shoes with a single inertial sensor and a smartphone application were developed as a gait monitoring system to detect users’ gait cycle, stand phase time, swing phase time, stride length, and foot clearance. We recruited 30 participants (24.09 ± 1.89 years) to collect gait data and used the Vicon motion capture system to verify the accuracy of the gait metrics. The results show that the gait monitoring system performs better on the assessment of the gait metrics. The accuracy of stride length and foot clearance is 96.17% and 92.07%, respectively. The artificial intelligence-empowered gait monitoring system holds promising potential for improving gait analysis and monitoring in the medical and healthcare fields. Full article

Tripping is the largest cause of falls, and low swing foot ground clearance during the mid-swing phase, particularly at the critical gait event known as Minimum Foot Clearance (MFC), is the major risk factor for tripping-related falls. Intervention strategies to increase MFC height can be effective if applied in real-time based on feed-forward prediction. The current study investigated the capability of machine learning models to classify the MFC into various categories using toe-off kinematics data. Specifically, three MFC sub-categories (less than 1.5 cm, between 1.5 and 2.0 cm, and higher than 2.0 cm) were predicted to apply machine learning approaches. A total of 18,490 swing phase gait cycles’ data were extracted from six healthy young adults, each walking for 5 min at a constant speed of 4 km/h on a motorized treadmill. K-Nearest Neighbor (KNN), Random Forest, and XGBoost were utilized for prediction based on the data from toe-off for five consecutive frames (0.025 s duration). Foot kinematics data were obtained from an inertial measurement unit attached to the mid-foot, recording tri-axial linear accelerations and angular velocities of the local coordinate. KNN, Random Forest, and XGBoost achieved 84%, 86%, and 75% accuracy, respectively, in classifying MFC into the three sub-categories with run times of 0.39 s, 13.98 s, and 170.98 s, respectively. The KNN-based model was found to be more effective if incorporated into an active exoskeleton as the intelligent system to control MFC based on the preceding gait event, i.e., toe-off, due to its quicker computation time. The machine learning-based prediction model shows promise for the prediction of critical MFC data, indicating higher tripping risk. Full article

The advancement in depth-sensor technology increased the potential for the clinical use of markerless three-dimensional motion analysis (3DMA); however, the accurate quantification of depth-sensor-based 3DMA on gait characteristics deviating from normal patterns is unclear. This study investigated the concurrent validity of the measurements of compensatory movements measured by depth-sensor-based 3DMA compared to those measured by marker-based 3DMA. We induced swing-phase compensatory movements due to insufficient toe clearance by restricting unilateral ankle and knee joint movements in healthy individuals. Thirty-two healthy young adults (nineteen males, aged 20.4$\pm$2.0 years, height 164.4$\pm$9.8 cm, weight 60.0$\pm$9.3 kg [average $\pm$ standard deviation]) walked the 6 m walkway in slow speed, very slow speed, and knee–ankle–foot orthosis (KAFO; participants wore KAFOs on the right leg) conditions. Gait kinematics were measured with marker-based and depth-sensor-based 3DMA systems. The intraclass correlation coefficient (ICC_3,1) was used to measure the relative agreement between depth-sensor-based and marker-based 3DMA and demonstrated good or moderate validity for swing-phase compensatory movement measurement. Additionally, the ICC_2,1 measured absolute agreement between the systems and showed lower validity than the ICC_3,1. The measurement errors for contralateral vaulting, trunk lateral flexion, hip hiking, swing-side hip abduction, and circumduction between instruments were 0.01 m, 1.30°, 1.99°, 2.37°, and 1.53°, respectively. Depth-sensor-based 3DMA is useful for determining swing-phase compensatory movements, although the possibility of missing a slight measurement error of 1–2° must be considered. Full article

Gait training to intentionally lengthen the nonparetic step length can increase the propulsive force of the paretic leg but may also induce overactivity of the knee extensor muscles that might limit knee flexion during the swing phase. Herein, we investigated the effects of lengthening the nonparetic step length during gait on the joint motion and muscle activity of the paretic lower limb. Fifteen chronic stroke patients (stroke group) and 15 healthy participants (control group) were evaluated for lower limb joint movements, electromyography, and spatiotemporal gait parameters during walking. Walking conditions were Normal (comfortable walking) and NP-Long/Contralateral-Long (walking with a lengthened step length of the nonmeasured limb). The trailing limb angle, a surrogate for propulsive forces, was increased in both groups by changing the step length, with no significant change in the peak knee flexion angle during the swing phase. However, the stroke group did not increase ankle plantar flexor activity in the stance phase or ankle dorsiflexion angle in the swing phase. Intentionally lengthening the nonparetic step length did not limit knee flexion. However, the effect of increased propulsive force during the stance phase was insufficient, with the possibility of decreased foot clearance. Full article

In healthy young adults, electrical stimulation of the superficial peroneal cutaneous nerve (SPn) innervating the dorsum of the foot has been shown to elicit functionally relevant reflexes during walking that are similar to those evoked by mechanical perturbation to the dorsum of the foot during walking and are referred to as stumble corrective (obstacle avoidance) responses. Though age-related differences in reflexes induced by mechanical perturbation have been studied, toe clearance has not been measured. Further, age-related differences in reflexes evoked by electrical stimulation of SPn have yet to be determined. Thus, the purpose of this study was to characterize age-related differences between healthy young adults and older adults with no history of falls in stumble correction responses evoked by electrical stimulation of the SPn at the ankle during walking. Toe clearance relative to the walking surface along with joint displacement and angular velocity at the ankle and knee and EMG of the tibialis anterior, medial gastrocnemius, biceps femoris and vastus lateralis were measured. The combined background and reflex toe clearance was reduced in the older adults compared with the young in mid-early swing (p = 0.011). These age-related differences likely increase fall risk in the older adult cohort. Further, age-related changes were seen in joint kinematics and EMG in older adults compared with the young such as decreased amplitude of the plantarflexion reflex in early swing in older adults (p < 0.05). These altered reflexes reflect the degradation of the stumble corrective response in older adults. Full article