Non-MTC gait cycles: An adaptive toe trajectory control strategy in older adults

Investigating the Effects of a Kinematic Gait Parameter-Based Haptic Cue on Toe Clearance in Parkinson's Patients

Recurrent falls pose a significant challenge for Parkinson's disease (PD) patients and are a leading cause of disability in this population. One contributing factor to these recurring falls is the reduced minimum toe clearance (mTC). Preventing such falls by enhancing mTC has become an important goal in gait training among PD patients. In this paper, we propose a wearable cueing-based novel gait training device in anticipation of improved mTC. The cueing device records the foot strike angle (FSA) and cues the participants if the FSA is observed above a threshold. The patients with PD (n = 8) were recruited and asked to walk under two conditions: (a) with cue and (b) without cue at a self-selected speed during the ON medication state. Kinetic and kinematic gait parameters such as vertical ground reaction force, center of pressure, toe clearance, and FSA were recorded. A Mann-Whitney U test showed a significant increase (p < 0.001) in the toe clearance (within 34% to 64% of the swing phase from the toe-off instance) and FSA, from 87.60 mm and - 5.43degrees respectively during without cue to 94.29 mm and 2.93degrees respectively during with cue walking condition except in one subject. These findings support the potential incorporation of an FSA-based cueing device for toe clearance improvement among PD patients. In addition, the wearable setup supports the cueing device applicability outside laboratory and home settings.

Estimation of minimum foot clearance using a single foot-mounted inertial sensor and personalized foot geometry scan

The real-world measurement of minimum foot clearance (mFC) during the swing phase of gait is critical in efforts to understand and reduce the risk of trip-and-fall incidents in populations with gait impairments. Past research has focused on measuring clearance of a single point on a person's foot, typically the toe-however, this may overestimate mFC and may even be the wrong region of the foot in cases of gait impairments or interventions. In this work, we present a novel method to reconstruct the swing-phase trajectory of an arbitrary number of points on a person's shoe and estimate the instantaneous height and location of whole-foot mFC. This is achieved using a single foot-mounted inertial sensor and personalized shoe geometry scan, assuming a rigid-body IMU-shoe system. This combination allows collection and analysis using out-of-lab tests, potentially including clinical environments. Validation of single marker location using the proposed method vs. motion capture showed height errors with bias less than 0.05 mm, and 95% confidence interval of - 8.18 to + 8.09 mm. The method is demonstrated in an example data set comparing different interventions for foot drop, and it shows clear differences among no intervention, functional electrical stimulation, and ankle-foot orthosis conditions. This method offers researchers and clinicians a rich understanding of a person's gait by providing objective 3D foot kinematics and allowing a unique opportunity to view the regions of the foot where minimum clearance occurs. This information can contribute to a more informed recommendation of specific interventions or assistive technology than is currently possible in standard clinical practice.

Fatigue Effect on Minimal Toe Clearance and Toe Activity during Walking

This study investigates the effects of fatigue on the process of walking in young adults using the developed clog-integrated sensor system. The developed sensor can simultaneously measure the forefoot activity (FA) and minimum toe clearance (MTC). The FA was evaluated through the change in the contact area captured by a camera using a method based on a light conductive plate. The MTC was derived from the distance between the bottom surface of the clog and ground obtained using a time of flight (TOF) sensor, and the clog posture was obtained using an acceleration sensor. The induced fatigue was achieved by walking on a treadmill at the fastest walking speed. We evaluated the FA and MTC before and after fatigue in both feet for 14 participants. The effects of fatigue manifested in either the FA or MTC of either foot when the results were evaluated by considering the participants individually, although individual variances in the effects of fatigue were observed. In the dominant foot, a significant increase in either the FA or MTC was observed in 13 of the 14 participants. The mean MTC in the dominant foot increased significantly (p = 0.038) when the results were evaluated by considering the participants as a group.

The effects of cognitive tasks on the frequency of non-MTC gait cycle during walking in healthy older and young adults

[Purpose] To investigate the effects of cognitive tasks on the non-minimum toe clearance gait cycles (nMTC) frequency during walking in healthy older and young adults. [Participants and Methods] This study included 20 healthy older and 20 young adults. The participants performed 3 min preferred-speed walking under a single-task and three dual-tasks (DTs) consisting of verbal, subtraction, and recall tasks. We determined the nMTC, which could not detect a trough in the toe trajectory during the swing phase. We evaluated the nMTC frequency (the cases of nMTC / total gait cycles) and compared them among the tasks and between groups. [Results] The results of the two-way analysis of variance revealed that there were no differences among the tasks, while the nMTC frequency in the older group was higher than that in the young group. The DT cost (DTc), which was used as an indicator of cognitive-motor interference (CMI), was higher in the subtraction and recall tasks in the older group than those in the young group. [Conclusion] This study showed that adding a cognitive task while walking increased in the nMTC frequency in older adults. These results suggest that the nMTC frequency under DT would reflect the increased CMI in healthy older adults.

The Stumblemeter: Design and Validation of a System That Detects and Classifies Stumbles during Gait

Stumbling during gait is commonly encountered in patients who suffer from mild to serious walking problems, e.g., after stroke, in osteoarthritis, or amputees using a lower leg prosthesis. Instead of self-reporting, an objective assessment of the number of stumbles in daily life would inform clinicians more accurately and enable the evaluation of treatments that aim to achieve a safer walking pattern. An easy-to-use wearable might fulfill this need. The goal of the present study was to investigate whether a single inertial measurement unit (IMU) placed at the shank and machine learning algorithms could be used to detect and classify stumbling events in a dataset comprising of a wide variety of daily movements. Ten healthy test subjects were deliberately tripped by an unexpected and unseen obstacle while walking on a treadmill. The subjects stumbled a total of 276 times, both using an elevating recovery strategy and a lowering recovery strategy. Subjects also performed multiple Activities of Daily Living. During data processing, an event-defined window segmentation technique was used to trace high peaks in acceleration that could potentially be stumbles. In the reduced dataset, time windows were labelled with the aid of video annotation. Subsequently, discriminative features were extracted and fed to train seven different types of machine learning algorithms. Trained machine learning algorithms were validated using leave-one-subject-out cross-validation. Support Vector Machine (SVM) algorithms were most successful, and could detect and classify stumbles with 100% sensitivity, 100% specificity, and 96.7% accuracy in the independent testing dataset. The SVM algorithms were implemented in a user-friendly, freely available, stumble detection app named Stumblemeter. This work shows that stumble detection and classification based on SVM is accurate and ready to apply in clinical practice.

Design and Validation of a Real-Time Visual Feedback System to Improve Minimum Toe Clearance (mTC) in Transfemoral Amputees

Tripping is accompanied by reduced minimum toe clearance (mTC) during the swing phase of gait. The risk of fall due to tripping among transfemoral amputees is nearly 67% which is greater than the transtibial amputees. Therefore, intervention to improve mTC can potentially enhance the quality of life among transfemoral amputees. In this paper, we first develop a real-time visual feedback system with center of pressure (CoP) information. Next, we recruited six non-disabled and three transfemoral amputees to investigate the effect on mTC while participants were trained to shift the CoP anteriorly/posteriorly during heel strike. Finally, to assess the lasting effect of training on mTC, retention trials were conducted without feedback. During feedback, posterior shift in the CoP improved the mTC significantly from 4.68 ± 0.40 cm to 6.12 ± 0.68 cm (p < 0.025) in non-disabled participants. A similar significant improvement in mTC from 4.60 ± 0.55 cm to 5.62 ± 0.57 cm was observed in amputees during posterior shift of CoP. Besides mTC, maximal toe clearances, i.e., maxTC₁ and maxTC₂, also showed a significant increase (p < 0.025) during the posterior shift of CoP in both the participants. Moreover, during retention, mTC did not differ significantly (p > 0.05) from feedback condition in amputee, suggesting a positive effect of feedback training. The foot-to-ground angle (FGA) at mTC increased significantly (p < 0.025) during posterior shift feedback in non-disabled suggests active ankle dorsiflexion in increasing mTC. However, in amputees, FGA at mTC did not differ significantly during both anterior and posterior CoP shift feedback. The present findings suggest CoP feedback as a potential strategy during gait rehabilitation of transfemoral amputees.

Effects of Visually Augmented Gait Training on Foot-Ground Clearance: An Intervention to Reduce Tripping-Related Falls

Minimum toe clearance (MTC ∼10-30 mm) is a hazardous mid-swing gait event, characterized by high-foot velocity (∼4.60 m·s-1) and single-foot support. This experiment tested treadmill-based gait training effects on MTC. Participants were 10 young (4 males and 6 females) and 10 older (6 males and 4 females) healthy ambulant individuals. The mean age, stature, and body mass for the younger group was 23 (2) years, 1.72 (0.10) m, and 67.5 (8.3) kg, and for older adults was 77 (9) years, 1.64 (0.10) m, and 71.1 (12.2) kg. Ten minutes of preferred speed treadmill walking (baseline) was followed by 20 minutes with MTC information (feedback) and 10 minutes without feedback (retention). There were no aging effects on MTC in baseline or feedback. The MTC in baseline for older adults was 14.2 (3.5) mm and feedback 27.5 (8.7) mm, and for the younger group, baseline was 12.7 (2.6) mm and feedback 28.8 (5.1) mm, respectively. Retention MTC was significantly higher for both groups, indicating a positive effect of augmented information: younger 40.8 (7.3) mm and older 27.7 (13.6) mm. Retention joint angles relative to baseline indicated that the young modulated joint angles control MTC differently using increased ankle dorsiflexion at toe off and modulating knee and hip angles later in swing closer to MTC.

Slower than normal walking speeds involve a pattern shift in joint and temporal coordination contributions

Kinematic and spatiotemporal gait parameters are known to scale with gait speed, though inter-joint coordination during swing remains consistent, at least across comfortable speeds. The purpose of this study was to determine whether coordination patterns serving limb clearance and shortening change across a range of gait speeds. We assessed 17 healthy adults walking overground at their self-selected speed and multiple, progressively slower speeds. We collected lower extremity kinematics with 3D motion analysis and quantified joint influence, or relative joint contributions, to limb clearance and shortening. We investigated changes in coordination using linear mixed models to determine magnitude and timing differences of joint influence across walking speeds. Joint influences serving limb clearance (hip, knee, and ankle) reduced considerably with slower walking speeds. Similarly, knee and ankle influences on limb shortening reduced with slower walking speeds. Temporally, joint influences on limb clearance varied across walking speeds. Notably, the temporal order of peak hip and knee influences reversed below typical self-selected walking speeds. For limb shortening, the timing of knee and ankle influences occurred later in the gait cycle as walking speed decreased. While relative joint contributions serve limb clearance and shortening scale with walking speeds, our results demonstrate that temporal coordination of limb clearance is altered in healthy individuals as walking speed falls below the range of typical self-selected walking speeds.

Foot-ground clearance characteristics in women: A comparison across different ages

BACKGROUND

Tripping is a common event leading to falls amongst elderly. Minimum foot clearance (MFC) is a critical swing phase control factor associated with tripping and falls.

RESEARCH QUESTION

Are there differences in MFC characteristics among three age groups of women and are there association between MFC and lower limb kinematics?

METHODS

Cross-sectional observational study. Three-dimensional gait analysis of 55 healthy women. ANOVA was used to compare (p<0.05) MFC characteristics among young, middle-aged and elderly groups. Multiple Linear Regression Analysis was used to test prediction over MFC.

RESULTS

Elderly women walked slower, with lower MFC and lower maximum foot velocity during swing (MFV) than young and middle-aged women. There were more hip flexion and less ankle dorsiflexion during MFC among elderly. There is a strong positive relationship between dorsiflexion and MFC. And ankle dorsiflexion was the most predictive variable over MFC.

SIGNIFICANCE

Elderly women walk slower with lower MFC value and less ankle dorsiflexion than gender-matched young controls. Increased hip flexion may represent a gait adaptation to avoid tripping. Gait speed had no effect on those findings.

A Principal Components Analysis Approach to Quantifying Foot Clearance and Foot Clearance Variability

Low foot clearance and high variability may be related to falls risk. Foot clearance is often defined as the local minimum in toe height during swing; however, not all strides have this local minimum. The primary purpose of this study was to identify a nondiscrete measure of foot clearance during all strides, and compare discrete and nondiscrete measures in ability to rank individuals on foot clearance and variability. Thirty-five participants (young adults [n = 10], older fallers [n = 10], older nonfallers [n = 10], and stroke survivors [n = 5]) walked overground while lower extremity 3D kinematics were recorded. Principal components analysis (PCA) of the toe height waveform yielded representation of toe height when it was closest to the ground. Spearman's rank order correlation assessed the association of foot clearance and variability between PCA and discrete variables, including the local minimum. PCA had significant (P < .05) moderate or strong associations with discrete measures of foot clearance and variability. An approximation of the discrete local minimum had a weak association with PCA and other discrete measures of foot clearance. A PCA approach to quantifying foot clearance can be used to identify the behavioral components of toe height when it is closest to the ground, even for strides without a local minimum.

A new measure of trip risk integrating minimum foot clearance and dynamic stability across the swing phase of gait

Minimum toe clearance (MTC) is thought to quantify the risk of the toe contacting the ground during the swing phase of gait and initiating a trip, but there are methodological issues with this measure and the risk of trip-related falls has been shown to also be associated with gait speed and dynamic stability. This paper proposes and evaluates a new measure, trip risk integral (TRI), that circumvents many issues with MTC as typically calculated at a single point by considering minimum foot clearance across the entire swing phase and taking into account dynamic stability to estimate risk of falling due to a trip rather than risk of the foot contacting the floor. Shoes and floor surfaces were digitized and MTC and TRI calculated for unimpaired younger (N=14, age=26±5), unimpaired older (N=14, age=73±7), and older adults who had recently fallen (N=11, age=72±5) walking on surfaces with no obstacles, visible obstacles, and hidden obstacles at slow, preferred, and fast gait speeds. MTC and TRI had significant (F≥5, p≤0.005) but differing effects of gait speed and floor surface. As gait speed increased (which increases risk of trip-related falls) MTC indicated less and TRI greater risk, indicating that TRI better quantifies risk of falling due to a trip. While MTC and TRI did not differ by subject group, strong speed-related effects of TRI (F≥8, p≤0.0007) resulted in improved TRI for fallers due to their slower self-selected preferred gait. This demonstrates that slower gait is both an important covariate and potential intervention for trip-related falls.