Synthesis of Walking Sounds for Alleviating Gait Disturbances in Parkinson’s Disease

Managing gait disturbances in people with Parkinson’s disease is a pressing challenge, as symptoms can contribute to injury and morbidity through an increased risk of falls. While drug-based interventions have limited efficacy in alleviating gait impairments, certain non-pharmacological methods, such as cueing, can also induce transient improvements to gait. The approach adopted here is to use computationally-generated sounds to help guide and improve walking actions. The first method described uses recordings of force data taken from the steps of a healthy adult which in turn were used to synthesize realistic gravel-footstep sounds that represented different spatio-temporal parameters of gait, such as step duration and step length. The second method described involves a novel method of sonifying, in real time, the swing phase of gait using real-time motion-capture data to control a sound synthesis engine. Both approaches explore how simple but rich auditory representations of action based events can be used by people with Parkinson’s to guide and improve the quality of their walking, reducing the risk of falls and injury. Studies with Parkinson’s disease patients are reported which show positive results for both techniques in reducing step length variability. Potential future directions for how these sound approaches can be used to manage gait disturbances in Parkinson’s are also discussed.

Auditory observation of stepping actions can cue both spatial and temporal components of gait in Parkinson's disease patients

Objectives: A common behavioural symptom of Parkinson’s disease (PD) is reduced step length (SL). Whilst sensory cueing strategies can be effective in increasing SL and reducing gait variability, current cueing strategies conveying spatial or temporal information are generally confined to the use of either visual or auditory cue modalities, respectively. We describe a novel cueing strategy using ecologically-valid ‘action-related’ sounds (footsteps on gravel) that convey both spatial and temporal parameters of a specific action within a single cue.
Methods: The current study used a real-time imitation task to examine whether PD affects the ability to re-enact changes in spatial characteristics of stepping actions, based solely on auditory information. In a second experimental session, these procedures were repeated using synthesized sounds derived from recordings of the kinetic interactions between the foot and walking surface. A third experimental session examined whether adaptations observed when participants walked to action-sounds were preserved when participants imagined either real recorded or synthesized sounds.
Results: Whilst healthy control participants were able to re-enact significant changes in SL in all cue conditions, these adaptations, in conjunction with reduced variability of SL were only observed in the PD group when walking to, or imagining the recorded sounds.
Conclusions: The findings show that while recordings of stepping sounds convey action information to allow PD patients to re-enact and imagine spatial characteristics of gait, synthesis of sounds purely from gait kinetics is insufficient to evoke similar changes in behaviour, perhaps indicating that PD patients have a higher threshold to cue sensorimotor resonant responses.

Gait period estimation algorithm based on the angles of extremities

Gait period estimation is an important step in the gait recognition framework. In this paper, we propose a new gait cycle detection method based on the angles of extreme points of both legs. In addition to that, to further improve the estimation of the gait period, the proposed algorithm divides the gait sequence into sections before identifying the maximum values. The proposed algorithm is scale invariant and less dependent on the silhouette shape. The performance of the proposed method was evaluated using the OU-ISIR speed variation gait database. The experimental results show that the proposed method achieved 90.2% gait recognition accuracy and outperforms previous methods found in the literature with the second best only achieved 67.65% accuracy.

The effect of the 'Gait keeper' mutation in the DMRT3 gene on gaiting ability in Icelandic horses

A nonsense mutation in DMRT3 ('Gait keeper' mutation) has a predominant effect on gaiting ability in horses, being permissive for the ability to perform lateral gaits and having a favourable effect on speed capacity in trot. The DMRT3 mutant allele (A) has been found in high frequency in gaited breeds and breeds bred for harness racing, while other horse breeds were homozygous for the wild-type allele (C). The aim of this study was to evaluate further the effect of the DMRT3 nonsense mutation on the gait quality and speed capacity in the multigaited Icelandic horse and demonstrate how the frequencies of the A- and C- alleles have changed in the Icelandic horse population in recent decades. It was confirmed that homozygosity for the DMRT3 nonsense mutation relates to the ability to pace. It further had a favourable effect on scores in breeding field tests for the lateral gait tölt, demonstrated by better beat quality, speed capacity and suppleness. Horses with the CA genotype had on the other hand significantly higher scores for walk, trot, canter and gallop, and they performed better beat and suspension in trot and gallop. These results indicate that the AA genotype reinforces the coordination of ipsilateral legs, with the subsequent negative effect on the synchronized movement of diagonal legs compared with the CA genotype. The frequency of the A-allele has increased in recent decades with a corresponding decrease in the frequency of the C-allele. The estimated frequency of the A-allele in the Icelandic horse population in 2012 was 0.94. Selective breeding for lateral gaits in the Icelandic horse population has apparently altered the frequency of DMRT3 genotypes with a predicted loss of the C-allele in relatively few years. The results have practical implications for breeding and training of Icelandic horses and other gaited horse breeds.

A frontal view gait recognition based on 3D imaging using a time of flight camera

Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.

Auditory cueing in Parkinson's patients with freezing of gait. What matters most: action-relevance or cue-continuity?

Gait disturbances are a common feature of Parkinson’s disease, one of the most severe being freezing of gait. Sensory cueing is a common method used to facilitate stepping in people with Parkinson’s. Recent work has shown that, compared to walking to a metronome, Parkinson’s patients without freezing of gait (nFOG) showed reduced gait variability when imitating recorded sounds of footsteps made on gravel. However, it is not known if these benefits are realised through the continuity of the acoustic information or the action-relevance. Furthermore, no study has examined if these benefits extend to PD with freezing of gait. We prepared four different auditory cues (varying in action-relevance and acoustic continuity) and asked 19 Parkinson’s patients (10 nFOG, 9 with freezing of gait (FOG)) to step in place to each cue. Results showed a superiority of action-relevant cues (regardless of cue-continuity) for inducing reductions in Step coefficient of variation (CV). Acoustic continuity was associated with a significant reduction in Swing CV. Neither cue-continuity nor action-relevance was independently sufficient to increase the time spent stepping before freezing. However, combining both attributes in the same cue did yield significant improvements. This study demonstrates the potential of using action-sounds as sensory cues for Parkinson’s patients with freezing of gait. We suggest that the improvements shown might be considered audio-motor ‘priming’ (i.e., listening to the sounds of footsteps will engage sensorimotor circuitry relevant to the production of that same action, thus effectively bypassing the defective basal ganglia).

On covariate factor detection and removal for robust gait recognition

We propose a novel bolt-on module capable of boosting the robustness of various single compact 2D gait representations. Gait recognition is negatively influenced by covariate factors including clothing and time which alter the natural gait appearance and motion. Contrary to traditional gait recognition, our bolt-on module remedies this by a dedicated covariate factor detection and removal procedure which we quantitatively and qualitatively evaluate. The fundamental concept of the bolt-on module is founded on exploiting the pixel-wise composition of covariate factors. Results demonstrate how our bolt-on module is a powerful component leading to significant improvements across gait representations and datasets yielding state-of-the-art results.

Dynamic Distance-Based Shape Features for Gait Recognition

We propose a novel skeleton-based approach to gait recognition using our Skeleton Variance Image. The core of our approach consists of employing the screened Poisson equation to construct a family of smooth distance functions associated with a given shape. The screened Poisson distance function approximation nicely absorbs and is relatively stable to shape boundary perturbations which allows us to define a rough shape skeleton. We demonstrate how our Skeleton Variance Image is a powerful gait cycle descriptor leading to a significant improvement over the existing state of the art gait recognition rate.

Let your feet do the walking: constraints on the stability of bipedal coordination

In this paper we consider whether the behaviour of the neural circuitry that controls lower limb movements in humans is shaped primarily by the spatiotemporal characteristics of bipedal gait patterns, or by selective pressures that are sensitive to considerations of balance and energetics. During the course of normal locomotion, the full dynamics of the neural circuitry are masked by the inertial properties of the limbs. In the present study, participants executed bipedal movements in conditions in which their feet were either unloaded or subject to additional inertial loads. Two patterns of rhythmic coordination were examined. In the in-phase mode, participants were required to flex their ankles and extend their ankles in synchrony. In the out-of-phase mode, the participants flexed one ankle while extending the other and vice versa. The frequency of movement was increased systematically throughout each experimental trial. All participants were able to maintain both the in-phase and the out-of-phase mode of coordination, to the point at which they could no longer increase their frequency of movement. Transitions between the two modes were not observed, and the stability of the out-of-phase and in-phase modes of coordination was equivalent at all movement frequencies. These findings indicate that, in humans, the behaviour of the neural circuitry underlying coordinated movements of the lower limbs is not constrained strongly by the spatiotemporal symmetries of bipedal gait patterns.