Dataset Information

A randomised controlled trial evaluating the effect of an individual auditory cueing device on freezing and gait speed in people with Parkinson's disease.

ABSTRACT: Parkinson's disease is a progressive neurological disorder resulting from a degeneration of dopamine producing cells in the substantia nigra. Clinical symptoms typically affect gait pattern and motor performance. Evidence suggests that the use of individual auditory cueing devices may be used effectively for the management of gait and freezing in people with Parkinson's disease. The primary aim of the randomised controlled trial is to evaluate the effect of an individual auditory cueing device on freezing and gait speed in people with Parkinson's disease.A prospective multi-centre randomised cross over design trial will be conducted. Forty-seven subjects will be randomised into either Group A or Group B, each with a control and intervention phase. Baseline measurements will be recorded using the Freezing of Gait Questionnaire as the primary outcome measure and 3 secondary outcome measures, the 10 m Walk Test, Timed "Up & Go" Test and the Modified Falls Efficacy Scale. Assessments are taken 3-times over a 3-week period. A follow-up assessment will be completed after three months. A secondary aim of the study is to evaluate the impact of such a device on the quality of life of people with Parkinson's disease using a qualitative methodology.The Apple iPod-Shuffle and similar devices provide a cost effective and an innovative platform for integration of individual auditory cueing devices into clinical, social and home environments and are shown to have immediate effect on gait, with improvements in walking speed, stride length and freezing. It is evident that individual auditory cueing devices are of benefit to people with Parkinson's disease and the aim of this randomised controlled trial is to maximise the benefits by allowing the individual to use devices in both a clinical and social setting, with minimal disruption to their daily routine.

SUBMITTER: Ledger S

PROVIDER: S-EPMC2630976 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

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A randomised controlled trial evaluating the effect of an individual auditory cueing device on freezing and gait speed in people with Parkinson's disease.

Ledger Sean S Galvin Rose R Lynch Deirdre D Stokes Emma K EK

BMC neurology 20081211

<h4>Background</h4>Parkinson's disease is a progressive neurological disorder resulting from a degeneration of dopamine producing cells in the substantia nigra. Clinical symptoms typically affect gait pattern and motor performance. Evidence suggests that the use of individual auditory cueing devices may be used effectively for the management of gait and freezing in people with Parkinson's disease. The primary aim of the randomised controlled trial is to evaluate the effect of an individual audit ...[more]

PMID: 19077238

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Project description:Parkinson's disease is the second most common neurodegenerative disease worldwide reducing cognitive and motoric abilities of affected persons. Freezing of Gait (FoG) is one of the severe symptoms that is observed in the late stages of the disease and considerably impairs the mobility of the person and raises the risk of falls. Due to the pathology and heterogeneity of the Parkinsonian gait cycle, especially in the case of freezing episodes, the detection of the gait phases with wearables is challenging in Parkinson's disease. This is addressed by introducing a state-automaton-based algorithm for the detection of the foot's motion phases using a shoe-placed inertial sensor. Machine-learning-based methods are investigated to classify the actual motion phase as normal or FoG-affected and to predict the outcome for the next motion phase. For this purpose, spatio-temporal gait and signal parameters are determined from the segmented movement phases. In this context, inertial sensor fusion is applied to the foot's 3D acceleration and rate of turn. Support Vector Machine (SVM) and AdaBoost classifiers have been trained on the data of 16 Parkinson's patients who had shown FoG episodes during a clinical freezing-provoking assessment course. Two clinical experts rated the video-recorded trials and marked episodes with festination, shank trembling, shuffling, or akinesia. Motion phases inside such episodes were labeled as FoG-affected. The classifiers were evaluated using leave-one-patient-out cross-validation. No statistically significant differences could be observed between the different classifiers for FoG detection (p>0.05). An SVM model with 10 features of the actual and two preceding motion phases achieved the highest average performance with 88.5 ± 5.8% sensitivity, 83.3 ± 17.1% specificity, and 92.8 ± 5.9% Area Under the Curve (AUC). The performance of predicting the behavior of the next motion phase was significantly lower compared to the detection classifiers. No statistically significant differences were found between all prediction models. An SVM-predictor with features from the two preceding motion phases had with 81.6 ± 7.7% sensitivity, 70.3 ± 18.4% specificity, and 82.8 ± 7.1% AUC the best average performance. The developed methods enable motion-phase-based FoG detection and prediction and can be utilized for closed-loop systems that provide on-demand gait-phase-synchronous cueing to mitigate FoG symptoms and to prevent complete motoric blockades.

Project description:Freezing-of-gait (FOG) and impaired walking are common features of Parkinson's disease (PD). Provision of external stimuli (cueing) can improve gait, however, many cueing methods are simplistic, increase task loading or have limited utility in a real-world setting. Closed-loop (automated) somatosensory cueing systems have the potential to deliver personalised, discrete cues at the appropriate time, without requiring user input. Further development of cue delivery methods and FOG-detection are required to achieve this. In this feasibility study, we aimed to test if FOG-initiated vibration cues applied to the lower-leg via wearable devices can improve gait in PD, and to develop real-time FOG-detection algorithms. 17 participants with Parkinson's disease and daily FOG were recruited. During 1 h study sessions, participants undertook 4 complex walking circuits, each with a different intervention: continuous rhythmic vibration cueing (CC), responsive cueing (RC; cues initiated by the research team in response to FOG), device worn with no cueing (NC), or no device (ND). Study sessions were grouped into 3 stages/blocks (A-C), separated by a gap of several weeks, enabling improvements to circuit design and the cueing device to be implemented. Video and onboard inertial measurement unit (IMU) data were analyzed for FOG events and gait metrics. RC significantly improved circuit completion times demonstrating improved overall performance across a range of walking activities. Step frequency was significantly enhanced by RC during stages B and C. During stage C, > 10 FOG events were recorded in 45% of participants without cueing (NC), which was significantly reduced by RC. A machine learning framework achieved 83% sensitivity and 80% specificity for FOG detection using IMU data. Together, these data support the feasibility of closed-loop cueing approaches coupling real-time FOG detection with responsive somatosensory lower-leg cueing to improve gait in PD.

Dataset Information

A randomised controlled trial evaluating the effect of an individual auditory cueing device on freezing and gait speed in people with Parkinson's disease.

Publications

A randomised controlled trial evaluating the effect of an individual auditory cueing device on freezing and gait speed in people with Parkinson's disease.

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