Freezing of gait and fall detection in Parkinson's disease using wearable sensors: a systematic review.
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ABSTRACT:
SUBMITTER: Silva de Lima AL
PROVIDER: S-EPMC5533840 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:Distinct gait characteristics like short steps and shuffling gait are prototypical signs commonly observed in Parkinson's disease. Routinely assessed by observation through clinicians, gait is rated as part of categorical clinical scores. There is an increasing need to provide quantitative measurements of gait, e.g. to provide detailed information about disease progression. Recently, we developed a wearable sensor-based gait analysis system as diagnostic tool that objectively assesses gait parameter in Parkinson's disease without the need of having a specialized gait laboratory. This system consists of inertial sensor units attached laterally to both shoes. The computed target of measures are spatiotemporal gait parameters including stride length and time, stance phase time, heel-strike and toe-off angle, toe clearance, and inter-stride variation from gait sequences. To translate this prototype into medical care, we conducted a cross-sectional study including 190 Parkinson's disease patients and 101 age-matched controls and measured gait characteristics during a 4x10 meter walk at the subjects' preferred speed. To determine intraindividual changes in gait, we monitored the gait characteristics of 63 patients longitudinally. Cross-sectional analysis revealed distinct spatiotemporal gait parameter differences reflecting typical Parkinson's disease gait characteristics including short steps, shuffling gait, and postural instability specific for different disease stages and levels of motor impairment. The longitudinal analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson's disease and corresponded to physician ratings. Taken together, we successfully show that wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson's disease. These data demonstrate the feasibility and applicability of objective wearable sensor-based gait measurement in Parkinson's disease reaching high technological readiness levels for both, large scale clinical studies and individual patient care.
| S-EPMC5636070 | biostudies-literature
Project description:Freezing of gait (FOG) is a paroxysmal gait disorder that often occurs at advanced stages of Parkinson's disease (PD). FOG consists of abrupt walking interruption and severe difficulty in locomotion with an increased risk of falling. Pathophysiological mechanisms underpinning FOG in PD are still unclear. However, advanced MRI and nuclear medicine studies have gained relevant insights into the pathophysiology of FOG in PD. Neuroimaging studies have demonstrated structural and functional abnormalities in a number of cortical and subcortical brain regions in PD patients with FOG. In this paper, we systematically review existing neuroimaging literature on the structural and functional brain changes described in PD patients with FOG, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We evaluate previous studies using various MRI techniques to estimate grey matter loss and white matter degeneration. Moreover, we review functional brain changes by examining functional MRI and nuclear medicine imaging studies. The current review provides up-to-date knowledge in this field and summarizes the possible mechanisms responsible for FOG in PD.
| S-EPMC6864177 | biostudies-literature
Project description:Background: Parkinson's disease (PD) is a common and disabling pathology that is characterized by both motor and non-motor symptoms and affects millions of people worldwide. The disease significantly affects quality of life of those affected. Many works in literature discuss the effects of the disease. The most promising trends involve sensor devices, which are low cost, low power, unobtrusive, and accurate in the measurements, for monitoring and managing the pathology. OBJECTIVES:This review focuses on wearable devices for PD applications and identifies five main fields: early diagnosis, tremor, body motion analysis, motor fluctuations (ON-OFF phases), and home and long-term monitoring. The concept is to obtain an overview of the pathology at each stage of development, from the beginning of the disease to consider early symptoms, during disease progression with analysis of the most common disorders, and including management of the most complicated situations (i.e., motor fluctuations and long-term remote monitoring). DATA SOURCES:The research was conducted within three databases: IEEE Xplore®, Science Direct®, and PubMed Central®, between January 2006 and December 2016. STUDY ELIGIBILITY CRITERIA:Since 1,429 articles were found, accurate definition of the exclusion criteria and selection strategy allowed identification of the most relevant papers. RESULTS:Finally, 136 papers were fully evaluated and included in this review, allowing a wide overview of wearable devices for the management of Parkinson's disease.
| S-EPMC5635326 | biostudies-literature
Project description:ObjectiveIt is unknown how sex affects the prevalence of freezing of gait (FOG). We conducted a systematic review and meta-analysis to establish the sex-specific prevalence of FOG in persons with Parkinson's disease (PD). In addition, we investigated whether men and women were represented accurately in intervention trials targeting FOG.MethodsWe queried the EMBASE and PubMed databases and identified 2637 articles. Of these, 16 epidemiological studies were included in the meta-analysis, and 51 intervention studies were included in the comparative analysis.ResultsIn total, 5702 persons were included in the final meta-analysis of epidemiological studies. The pooled estimate of overall FOG prevalence was 43% [95% CI 33-53%]. We found no difference in FOG prevalence between men [44% (34-54%)] and women [42% (31-52%)] with PD. However, women were markedly underrepresented in intervention trials targeting FOG, with an average proportion of only 29.6% of women in trial populations. The percentage of women included in trials was similar across intervention types but differed greatly across geographical regions.ConclusionSex is not a predictor of FOG. This could aid clinicians in counseling persons with PD about FOG. Importantly, a global effort is needed to include more women into clinical trials. Given the skewed distribution of men and women included in intervention trials targeting FOG, caution might be warranted when extrapolating results from FOG trials to women.
| S-EPMC7815550 | biostudies-literature
Project description:External visual cueing is a well-known means to target freezing of gait (FOG) in Parkinson's disease patients. Holocue is a wearable visual cueing application that allows the HoloLens 1 mixed-reality headset to present on-demand patient-tailored action-relevant 2D and 3D holographic visual cues in free-living environments. The aim of this study involving 24 Parkinson's disease patients with dopaminergic "ON state" FOG was two-fold. First, to explore unfamiliarity and habituation effects associated with wearing the HoloLens on FOG. Second, to evaluate the potential immediate effect of Holocue on alleviating FOG in the home environment. Three sessions were conducted to examine (1) the effect of wearing the unfamiliar HoloLens on FOG by comparing walking with and without the HoloLens, (2) habituation effects to wearing the HoloLens by comparing FOG while walking with HoloLens over sessions, and (3) the potential immediate effect of Holocue on FOG by comparing walking with HoloLens with and without Holocue. Wearing the HoloLens (without Holocue) did significantly increase the number and duration of FOG episodes, but this unfamiliarity effect disappeared with habituation over sessions. This not only emphasizes the need for sufficient habituation to unfamiliar devices, but also testifies to the need for research designs with appropriate control conditions when examining effects of unfamiliar wearable cueing devices. Holocue had overall no immediate effect on FOG, although objective and subjective benefits were observed for some individuals, most notably those with long and/or many FOG episodes. Our participants raised valuable opportunities to improve Holocue and confirmed our assumptions about current and anticipated future design choices, which supports ongoing Holocue development for and with end users.
| S-EPMC8784874 | biostudies-literature
Project description:The use of wearable sensors allows continuous recordings of physical activity from participants in free-living or at-home clinical studies. The large amount of data collected demands automatic analysis pipelines to extract gait parameters that can be used as clinical endpoints. We introduce a deep learning-based automatic pipeline for wearables that processes tri-axial accelerometry data and extracts gait events-bout segmentation, initial contact (IC), and final contact (FC)-from a single sensor located at either the lower back (near L5), shin or wrist. The gait events detected are posteriorly used for gait parameter estimation, such as step time, length, and symmetry. We report results from a leave-one-subject-out (LOSO) validation on a pilot study dataset of five participants clinically diagnosed with Parkinson's disease (PD) and six healthy controls (HC). Participants wore sensors at three body locations and walked on a pressure-sensing walkway to obtain reference gait data. Mean absolute errors (MAE) for the IC events ranged from 22.82 to 33.09 milliseconds (msecs) for the lower back sensor while for the shin and wrist sensors, MAE ranges were 28.56-64.66 and 40.19-72.50 msecs, respectively. For the FC-event detection, MAE ranges were 29.06-48.42, 40.19-72.70 and 36.06-60.18 msecs for the lumbar, wrist and shin sensors, respectively. Intraclass correlation coefficients, ICC(2,k), between the estimated parameters and the reference data resulted in good-to-excellent agreement (ICC ≥ 0.84) for the lumbar and shin sensors, excluding the double support time (ICC = 0.37 lumbar and 0.38 shin) and swing time (ICC = 0.55 lumbar and 0.59 shin). The wrist sensor also showed good agreements, but the ICCs were lower overall than for the other two sensors. Our proposed analysis pipeline has the potential to extract up to 100 gait-related parameters, and we expect our contribution will further support developments in the fields of wearable sensors, digital health, and remote monitoring in clinical trials.
| S-EPMC8707484 | biostudies-literature
Project description:Freezing of gait (FOG) in Parkinson's disease (PD) causes severe patient burden despite pharmacological management. Exercise and training are therefore advocated as important adjunct therapies. In this meta-analysis, we assess the existing evidence for such interventions to reduce FOG, and further examine which type of training helps the restoration of gait function in particular. The primary meta-analysis across 41 studies and 1838 patients revealed a favorable moderate effect size (ES = -0.37) of various training modalities for reducing subjective FOG-severity (p < 0.00001), though several interventions were not directly aimed at FOG and some included non-freezers. However, exercise and training also proved beneficial in a secondary analysis on freezers only (ES = -0.32, p = 0.007). We further revealed that dedicated training aimed at reducing FOG episodes (ES = -0.24) or ameliorating the underlying correlates of FOG (ES = -0.40) was moderately effective (p < 0.01), while generic exercises were not (ES = -0.14, p = 0.12). Relevantly, no retention effects were seen after cessation of training (ES = -0.08, p = 0.36). This review thereby supports the implementation of targeted training as a treatment for FOG with the need for long-term engagement.
| S-EPMC8433229 | biostudies-literature
Project description:Freezing of gait (FOG) is a leading cause of falls and fractures in Parkinson's disease (PD). The episodic and rather unpredictable occurrence of FOG, coupled with the variable response to l-DOPA of this gait disorder, makes the objective evaluation of FOG severity a major clinical challenge in the therapeutic management of patients with PD. The aim of this study was to examine and compare gait, clinically and objectively, in patients with PD, with and without FOG, by means of a new wearable system. We also assessed the effect of l-DOPA on FOG severity and specific spatiotemporal gait parameters in patients with and without FOG. To this purpose, we recruited 28 patients with FOG, 16 patients without FOG, and 16 healthy subjects. In all participants, gait was evaluated clinically by video recordings and objectively by means of the wearable wireless system, during a modified 3-m Timed Up and Go (TUG) test. All patients performed the modified TUG test under and not under dopaminergic therapy (ON and OFF therapy). By comparing instrumental data with the clinical identification of FOG based on offline video-recordings, we also assessed the performance of the wearable system to detect FOG automatically in terms of sensitivity, specificity, positive and negative predictive values, and finally accuracy. TUG duration was longer in patients than in controls, and the amount of gait abnormalities was prominent in patients with FOG compared with those without FOG. l-DOPA improved gait significantly in patients with PD and particularly in patients with FOG mainly by reducing FOG duration and increasing specific spatiotemporal gait parameters. Finally, the overall wireless system performance in automatic FOG detection was characterized by excellent sensitivity (93.41%), specificity (98.51%), positive predictive value (89.55%), negative predictive value (97.31%), and finally accuracy (98.51%). Our study overall provides new information on the beneficial effect of l-DOPA on FOG severity and specific spatiotemporal gait parameters as objectively measured by a wearable sensory system. The algorithm here reported potentially opens to objective long-time sensing of FOG episodes in patients with PD.
| S-EPMC5557738 | biostudies-literature
Project description:Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.
| S-EPMC8069962 | biostudies-literature
Project description:OBJECTIVES:Wearable technology is increasingly used to monitor neurological disorders. The purpose of this systematic review was to synthesize knowledge from quantitative and qualitative clinical researches using wearable sensors in epilepsy, Parkinson's disease (PD), and stroke. METHODS:A systematic literature search was conducted in PubMed and Scopus spanning from 1995 to January 2017. A synthesis of the main findings, reported adherence to wearables and missing data from quantitative studies, is provided. Clinimetric properties of measures derived from wearables in laboratory, free activities in hospital, and free-living environment were also evaluated. Qualitative thematic synthesis was conducted to explore user experiences and acceptance of wearables. RESULTS:In total, 56 studies (50 reporting quantitative and 6 reporting qualitative data) were included for data extraction and synthesis. Among studies reporting quantitative data, 5 were in epilepsy, 21 PD, and 24 studies in stroke. In epilepsy, wearables are used to detect and differentiate seizures in hospital settings. In PD, the focus is on quantification of cardinal motor symptoms and medication-evoked adverse symptoms in both laboratory and free-living environment. In stroke upper extremity activity, walking and physical activity have been studied in laboratory and during free activities. Three analytic themes emerged from thematic synthesis of studies reporting qualitative data: acceptable integration in daily life, lack of confidence in technology, and the need to consider individualization. CONCLUSIONS:Wearables may provide information of clinical features of interest in epilepsy, PD and stroke, but knowledge regarding the clinical utility for supporting clinical decision making remains to be established.
| S-EPMC6060770 | biostudies-literature