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1.
J Neurol ; 2020 Feb 11.
Artigo em Inglês | MEDLINE | ID: mdl-32048014

RESUMO

BACKGROUND: Impaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments. OBJECTIVE: To objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington's Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC). METHODS: Patients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defined gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV). RESULTS: Stride length (- 15%) and gait velocity (- 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ rSp ≤ 0.690). Objective gait variability parameters correlated with disease stage based upon TFC. CONCLUSIONS: Sensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.

2.
Artigo em Inglês | MEDLINE | ID: mdl-32086225

RESUMO

Mobile gait analysis using wearable inertial measurement units (IMUs) provides valuable insights for the assessment of movement impairments in different neurological and musculoskeletal diseases, for example Parkinson's disease (PD). The increase in data volume due to arising long-term monitoring requires valid, robust and efficient analysis pipelines. In many studies an upstream detection of gait is therefore applied. However, current methods do not provide a robust way to successfully reject non-gait signals. Therefore, we developed a novel algorithm for the detection of gait from continuous inertial data of sensors worn at the feet. The algorithm is focused not only on a high sensitivity but also a high specificity for gait. Sliding windows of IMU signals recorded from the feet of PD patients were processed in the frequency domain. Gait was detected if the frequency spectrum contained specific patterns of harmonic frequencies. The approach was trained and evaluated on 150 clinical measurements containing standardized gait and cyclic movement tests. The detection reached as sensitivity of 0.98 and a specificity of 0.96 for the best sensor configuration (angular rate around the medio-lateral axis). On an independent validation data set including 203 unsupervised, semi-standardized gait tests, the algorithm achieved a sensitivity of 0.97. Our algorithm for the detection of gait from continuous IMU signals works reliably and showed promising results for the application in the context of free-living and non-standardized monitoring scenarios.

3.
Eur J Cancer Care (Engl) ; : e13199, 2019 Dec 12.
Artigo em Inglês | MEDLINE | ID: mdl-31829481

RESUMO

OBJECTIVE: Gait is a sensitive marker for functional declines commonly seen in patients treated for advanced cancer. We tested the effect of a combined exercise and nutrition programme on gait parameters of advanced-stage cancer patients using a novel wearable gait analysis system. METHODS: Eighty patients were allocated to a control group with nutritional support or to an intervention group additionally receiving whole-body electromyostimulation (WB-EMS) training (2×/week). At baseline and after 12 weeks, physical function was assessed by a biosensor-based gait analysis during a six-minute walk test, a 30-s sit-to-stand test, a hand grip strength test, the Karnofsky Index and EORTC QLQ-C30 questionnaire. Body composition was measured by bioelectrical impedance analysis and inflammation by blood analysis. RESULTS: Final analysis included 41 patients (56.1% male; 60.0 ± 13.0 years). After 12 weeks, the WB-EMS group showed higher stride length, gait velocity (p < .05), six-minute walking distance (p < .01), bodyweight and skeletal muscle mass, and emotional functioning (p < .05) compared with controls. Correlations between changes in gait and in body composition, physical function and inflammation were detected. CONCLUSION: Whole-body electromyostimulation combined with nutrition may help to improve gait and functional status of cancer patients. Sensor-based mobile gait analysis objectively reflects patients' physical status and could support treatment decisions.

4.
J Neurol Phys Ther ; 43(4): 224-232, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31517749

RESUMO

BACKGROUND AND PURPOSE: Perturbation training is a promising approach to reduce fall incidence in persons with Parkinson disease (PwPD). This study aimed to evaluate interindividual differences in balance adaptations in response to perturbation treadmill training (PTT) and identify potential outcome predictors. METHODS: PwPD (n = 43, Hoehn & Yahr stage 1-3.5) were randomly assigned to either 8 weeks of PTT or conventional treadmill training (CTT) without perturbations. At baseline and following intervention, data from 4 domains of balance function (reactive, anticipatory, dynamic postural control, and quiet stance) were collected. Using responder analysis we investigated interindividual differences (responder rates and magnitude of change) and potential predictive factors. RESULTS: PTT showed a significantly higher responder rate in the Mini Balance Evaluation Systems Test (Mini-BESTest) subscore reactive postural control, compared with CTT (PTT = 44%; CTT = 10%; risk ratio = 4.22, confidence interval = 1.03-17.28). Additionally, while between-groups differences were not significant, the proportion of responders in the measures of dynamic postural control was higher for PTT compared with CTT (PTT: 22%-39%; CTT: 5%-10%). The magnitude of change in responders and nonresponders was similar in both groups. PTT responders showed significantly lower initial balance performance (4/8 measures) and cognitive function (3/8 measures), and were older and at a more advanced disease stage, based on descriptive evaluation. DISCUSSION AND CONCLUSIONS: Our findings suggest that PTT is beneficial to improve reactive balance in PwPD. Further, PTT appeared to be effective only for a part of PwPD, especially for those with lower balance and cognitive function, which needs further attention.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A1).

5.
Artigo em Inglês | MEDLINE | ID: mdl-31449035

RESUMO

Hereditary spastic paraplegias (HSP) represents a group of orphan neurodegenerative diseases with gait disturbance as the predominant clinical feature. Due to its rarity, research within this field is still limited. Aside from clinical analysis using established scales, gait analysis has been employed to enhance the understanding of the mechanisms behind the disease. However, state of the art gait analysis systems are often large, immobile and expensive. To overcome these limitations, this paper presents the first clinically relevant mobile gait analysis system for HSP patients. We propose an unsupervised model based on local cyclicity estimation and hierarchical hidden Markov models (LCE-hHMM). The system provides stride time, swing time, stance time, swing duration and cadence. These parameters are validated against a GAITRite® system and manual sensor data labelling using a cohort of 24 patients within 2 separate studies. The proposed system achieves a stride time error of -0.00 ± 0.09 s (correlation coefficient, r = 1.00) and a swing duration error of -0.67 ± 3.27 % (correlation coefficient, r = 0.93) with respect to the GAITRite® system. We show that these parameters are also correlated to the clinical spastic paraplegia rating scale (SPRS) in a similar manner to other state of the art gait analysis systems, as well as to supervised and general versions of the proposed model. Finally, we show a proof of concept for this system to be used to analyse alterations in the gait of individual patients. Thus, with further clinical studies, due to its automated approach and mobility, this system could be used to determine treatment effects in future clinical trials.

6.
J Parkinsons Dis ; 2019 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-31424420

RESUMO

BACKGROUND: Parkinson's disease (PD) is an age dependent neurodegenerative disorder with increasing prevalence. Digital technologies like computers and smartphones offer mobile telecommunication, diagnostic and monitoring and may connect the patient continuously with his healthcare team, providing disease related information, and support healthcare. Since the use of these technologies in western civilization is age dependent, possession and usage cannot be regarded as given in PD. In contrast to increasing efforts to implement digital technology into PD patient care, little is known about the use of computers, smartphones, and internet-affinity in PD patients. OBJECTIVE: We evaluated the use of digital technologies in different age groups of PD patients. METHODS: We developed a questionnaire adapted to the annual German microcensus on "use of digital communication technologies", allowing a comparison to the general population in Germany. RESULTS: 190 PD patients completed the questionnaire. About 75% of PD patients access disease related information on the internet. Patients across all age groups used computers and the internet as frequent or more frequently compared to the German population. Use of computers, smartphones, and the internet in PD was age dependent. Advanced PD patients with higher motor impairment used smartphones less often, while mobile phone usage was not reduced. CONCLUSION: The adoption of a digital lifestyle is present in the PD population, apart from smartphone usage, which is impaired by motor symptoms. Thus, future healthcare technologies are not hampered by the inability of PD patients to use the necessary tools, however, fine motor-skill requirements have to be acknowledged.

7.
Sensors (Basel) ; 19(14)2019 Jul 13.
Artigo em Inglês | MEDLINE | ID: mdl-31337067

RESUMO

Mobile gait analysis systems using wearable sensors have the potential to analyze and monitor pathological gait in a finer scale than ever before. A closer look at gait in Parkinson's disease (PD) reveals that turning has its own characteristics and requires its own analysis. The goal of this paper is to present a system with on-shoe wearable sensors in order to analyze the abnormalities of turning in a standardized gait test for PD. We investigated turning abnormalities in a large cohort of 108 PD patients and 42 age-matched controls. We quantified turning through several spatio-temporal parameters. Analysis of turn-derived parameters revealed differences of turn-related gait impairment in relation to different disease stages and motor impairment. Our findings confirm and extend the results from previous studies and show the applicability of our system in turning analysis. Our system can provide insight into the turning in PD and be used as a complement for physicians' gait assessment and to monitor patients in their daily environment.


Assuntos
Algoritmos , Monitorização Fisiológica/instrumentação , Doença de Parkinson/fisiopatologia , Sapatos , Dispositivos Eletrônicos Vestíveis , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , Desenho de Equipamento , Feminino , Transtornos Neurológicos da Marcha/diagnóstico , Transtornos Neurológicos da Marcha/fisiopatologia , Humanos , Masculino , Pessoa de Meia-Idade , Monitorização Fisiológica/métodos , Monitorização Fisiológica/normas , Reprodutibilidade dos Testes , Análise Espaço-Temporal
8.
J Neuroeng Rehabil ; 16(1): 98, 2019 Jul 26.
Artigo em Inglês | MEDLINE | ID: mdl-31349860

RESUMO

The original article [1] contained an error whereby Fig. 6 contained a minor shading glitch affecting its presentation. This has now been corrected.

9.
J Neuroeng Rehabil ; 16(1): 77, 2019 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-31242915

RESUMO

BACKGROUND: Gait symptoms and balance impairment are characteristic indicators for the progression in Parkinson's disease (PD). Current gait assessments mostly focus on straight strides with assumed constant velocity, while acceleration/deceleration and turning strides are often ignored. This is either due to the set up of typical clinical assessments or technical limitations in capture volume. Wearable inertial measurement units are a promising and unobtrusive technology to overcome these limitations. Other gait phases such as initiation, termination, transitioning (between straight walking and turning) and turning might be relevant as well for the evaluation of gait and balance impairments in PD. METHOD: In a cohort of 119 PD patients, we applied unsupervised algorithms to find different gait clusters which potentially include the clinically relevant information from distinct gait phases in the standardized 4x10 m gait test. To clinically validate our approach, we determined the discriminative power in each gait cluster to classify between impaired and unimpaired PD patients and compared it to baseline (analyzing all straight strides). RESULTS: As a main result, analyzing only one of the gait clusters constant, non-constant or turning led in each case to a better classification performance in comparison to the baseline (increase of area under the curve (AUC) up to 19% relative to baseline). Furthermore, gait parameters (for turning, constant and non-constant gait) that best predict motor impairment in PD were identified. CONCLUSIONS: We conclude that a more detailed analysis in terms of different gait clusters of standardized gait tests such as the 4x10 m walk may give more insights about the clinically relevant motor impairment in PD patients.

10.
J Parkinsons Dis ; 9(2): 413-426, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30958316

RESUMO

BACKGROUND: Impaired gait and postural stability are cardinal motor symptoms in Parkinson's disease (PD). Treadmill training improves gait characteristics in PD. OBJECTIVE: This study investigates if postural perturbations during treadmill training improve motor performance and particularly gait and postural stability in PD. METHODS: This work presents secondary outcome measures of a pilot randomized controlled trial. PD patients (n = 43) recruited at the University Hospital Erlangen were randomly allocated to the experimental (perturbation treadmill training, PTT, n = 21) or control group (conventional treadmill training, CTT, n = 22). Outcome measures were collected at baseline, after 8 weeks of intervention, and 3 months follow-up. Motor impairment was assessed by the Unified Parkinson Disease Rating Scale part-III (UPDRS-III), Postural Instability and Gait Difficulty score (PIGD), and subitems 'Gait' and 'Postural stability' by an observer blinded to the randomization. Intervention effects were additionally compared to progression rates of a matched PD cohort (n = 20) receiving best medical treatment (BMT). RESULTS: Treadmill training significantly improved UPDRS-III motor symptoms in both groups with larger effect sizes for PTT (-38%) compared to CTT (-20%). In the PTT group solely, PIGD -34%, and items 'Gait' -50%, and 'Postural stability' -40% improved significantly in comparison to CTT (PIGD -24%, 'Gait' -22%, 'Postural stability' -33%). Positive effects persisted in PTT after 3 months and appeared to be beneficial compared to BMT. CONCLUSIONS: Eight weeks of PTT showed superior improvements of motor symptoms, particularly gait and postural stability. Sustainable effects indicate that PTT may be an additive therapy option for gait and balance deficits in PD.

11.
Front Neurol ; 10: 5, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30723450

RESUMO

Background: Differentiating idiopathic Parkinson's disease (IPD) from atypical Parkinsonian disorders (APD) is challenging, especially in early disease stages. Postural instability and gait difficulty (PIGD) are substantial motor impairments of IPD and APD. Clinical evidence implies that patients with APD have larger PIGD impairment than IPD patients. Sensor-based gait analysis as instrumented bedside test revealed more gait deficits in APD compared to IPD. However, the diagnostic value of instrumented bedside tests compared to clinical assessments in differentiating APD from IPD patients have not been evaluated so far. Objective: The objectives were (a) to evaluate whether sensor-based gait parameters provide additional information to validated clinical scores in differentiating APD from matched IPD patients, and (b) to investigate if objective, instrumented gait assessments have comparable discriminative power to clinical scores. Methods: In a previous study we have recorded instrumented gait parameters in patients with APD (Multiple System Atrophy and Progressive Supranuclear Palsy). Here, we compared gait parameters to those of retrospectively pairwise disease duration-, age-, and gender-matched IPD patients in order to address this new research questions. To this aim, the PIGD score was calculated as sum of the MDS-UPDRS-3-items "gait," "postural stability," "arising from chair," and "posture." Gait characteristics were evaluated in standardized gait tests using an instrumented, sensor-based gait analysis system. Machine learning algorithms were used to extract spatio-temporal gait parameters. Receiver Operating Characteristic analysis was performed in order to detect the discriminative power of the instrumented vs. the clinical bedside tests in differentiating IPD from APD. Results: Sensor-based stride length, gait velocity, toe off angle, and parameters representing gait variability significantly differed between IPD and APD groups. ROC analysis revealed a high Area Under the Curve (AUC) for PIGD score (0.919), and UPDRS-3 (0.848). Particularly, the objective parameters stance time variability (0.841), swing time variability (0.834), stride time variability (0.821), and stride length variability (0.804) reached high AUC's as well. Conclusions: PIGD symptoms showed high discriminative power in differentiating IPD from APD supporting gait disorders as substantial diagnostic target. Sensor-based gait variability parameters provide metric, objective added value, and serve as complementary outcomes supporting clinical diagnostics and long-term home-monitoring concepts.

12.
Hum Mov Sci ; 64: 123-132, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30711905

RESUMO

BACKGROUND: Gait impairment is a major motor symptom in Parkinson's disease (PD), and treadmill training is an effective non-pharmacological treatment option. RESEARCH QUESTION: In this study, the time course, sustainability and transferability of gait adaptations to treadmill training with and without additional postural perturbations were investigated. METHODS: 38 PD patients (Hoehn & Yahr 1-3.5) were randomly allocated to eight weeks of treadmill training, performed twice-weekly for 40 min either with (perturbation treadmill training [PTT], n = 18) or without (conventional treadmill training [CTT], n = 20) additional perturbations to the treadmill surface. Spatiotemporal gait parameters were assessed during treadmill walking on a weekly basis (T0-T8), and after three months follow-up (T9). Additional overground gait analyses were performed at T0 and T8 to investigate transfer effects. RESULTS: Treadmill gait variability reduced linearly over the course of 8 weeks in both groups (p < .001; Cohen's d (range): -0.53 to -0.84). Only the PTT group significantly improved in other gait parameters (stride length/time, stance-/swing time), with stride time showing a significant between-group interaction effect (Cohen's d = 0.33; p = .05). Additional between-group interactions indicated more sustained improvements in stance (Cohen's d = 0.85; p = .02) and swing time variability in the PTT group (Cohen's d = 0.82; p = .03) at T9. Overground gait improvements at T8 existed only in stance (d = -0.73; p = .04) and swing time (d = 0.73; p = .04). DISCUSSION: Treadmill stride-to-stride variability reduced substantially and linearly, but transfer to overground walking was limited. Adding postural perturbations tended to increase efficacy and sustainability of several gait parameters. However, since between-group effects were small, more work is necessary to support these findings.


Assuntos
Doença de Parkinson/fisiopatologia , Caminhada/fisiologia , Adaptação Fisiológica/fisiologia , Idoso , Teste de Esforço/métodos , Feminino , Marcha/fisiologia , Análise da Marcha/métodos , Transtornos Neurológicos da Marcha , Humanos , Masculino , Resultado do Tratamento
13.
Mult Scler Relat Disord ; 39: 101903, 2019 Dec 23.
Artigo em Inglês | MEDLINE | ID: mdl-31927199

RESUMO

BACKGROUND: Gait deficits are common in multiple sclerosis (MS) and contribute to disability but may not be easily detected in the early stages of the disease. OBJECTIVES: We investigated whether sensor-based gait analysis is able to detect gait impairments in patients with MS (PwMS). METHODS: A foot-worn sensor-based gait analysis system was used in 102 PwMS and 22 healthy controls (HC) that were asked to perform the 25-foot walking test (25FWT) two times in a self-selected speed (25FWT_pref), followed by two times in a speed as fast as possible (25FWT_fast). The Multiple Sclerosis Walking Scale (MSWS-12) was used as a subjective measure of patient mobility. Patients were divided into EDSS and functional system subgroups. RESULTS: Datasets between two consecutive measurements (test-retest-reliability) were highly correlated in all analysed mean gait parameters (e.g. 25FWT_fast: stride length r = 0.955, gait speed r = 0.969) Subgroup analysis between HC and PwMS with lower (EDSS≤3.5) and higher (EDSS 4.0-7.0) disability showed significant differences in mean stride length, gait speed, toe off angle, stance time and swing time (e.g. stride length of EDSS subgroups 25FWT_fast p ≤ 0.001, 25FWT_pref p = 0.003). The differences between EDSS subgroups were more pronounced in fast than in self-selected gait speed (e.g. stride length 25FWT_fast 33.6 cm vs. 25FWT_pref 16.3 cm). Stride length (25FWT_fast) highly correlated to EDSS (r=-0.583) and MSWS-12 (r=-0.668). We observed significant differences between HC and PwMS with (FS 0-1) and without (FS≥2) pyramidal or cerebellar disability (e.g. gait speed of FS subgroups p ≤ 0.001). CONCLUSION: Sensor-based gait analysis objectively supports the clinical assessment of gait abnormalities even in the lower stages of MS, especially when walking with fast speed. Stride length and gait speed where identified as the most clinically relevant gait measures. Thus, it may be used to support the assessment of PwMS with gait impairment in the future, e.g. for more objective classification of disability. Its role in home-monitoring scenarios need to be evaluated in further studies.

14.
Conf Proc IEEE Eng Med Biol Soc ; 2019: 309-312, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31945903

RESUMO

Recent studies showed that Parkinson's disease (PD) patients improved their gait parameters while walking with rhythmic auditory stimulation (RAS). They achieved a longer stride length, a reduced stride time variability and a higher walking speed. Combining RAS with mobile gait analysis would allow continuous monitoring of RAS effects and gait in natural environments. This paper proposes a mobile solution for home-based assessment of RAS by combining RAS gait training and a mobile system for data acquisition. Existing datasets were used to investigate the cadence of PD patients and to propose suitable frequencies for RAS gait training. The cadence calculation was implemented using a peak detection algorithm, which uses the time difference between two mid-swing events as stride time values. We validated our system as a whole using a cohort of 13 PD patients who performed RAS gait training. The algorithms were also validated against the eGaIT system, a state-of-the-art system, and achieved a mean F1 score for detected strides of 97.57 % ± 0.86 % and a mean absolute error for the cadence of 0.16 spm ± 0.09 spm. This study lays the ground work for further clinical studies investigating the effectiveness of mobile RAS within a home environment.


Assuntos
Transtornos Neurológicos da Marcha , Marcha , Doença de Parkinson , Estimulação Acústica , Humanos , Velocidade de Caminhada
15.
Gait Posture ; 66: 194-200, 2018 10.
Artigo em Inglês | MEDLINE | ID: mdl-30199778

RESUMO

BACKGROUND: Despite the general success of total knee arthroplasty (TKA) regarding patient-reported outcome measures, studies investigating gait function have shown diverse functional outcomes. Mobile sensor-based systems have recently been employed for accurate clinical gait assessments, as they allow a better integration of gait analysis into clinical routines as compared to laboratory based systems. RESEARCH QUESTION: In this study, we sought to examine whether an accurate assessment of gait function of knee osteoarthritis patients with respect to surgery outcome evaluation after TKA using a mobile sensor-based gait analysis system is possible. METHODS: A foot-worn sensor-based system was used to assess spatio-temporal gait parameters of 24 knee osteoarthritis patients one day before and one year after TKA, and in comparison to matched control participants. Patients were clustered into positive and negative responder groups using a heuristic approach regarding improvements in gait function. Machine learning was used to predict surgery outcome based on pre-operative gait parameters. RESULTS: Gait function differed significantly between controls and patients. Patient-reported outcome measures improved significantly after surgery, but no significant global gait parameter difference was observed between pre- and post-operative status. However, the responder groups could be correctly predicted with an accuracy of up to 89% using pre-operative gait parameters. Patients exhibiting high pre-operative gait function were more likely to experience a functional decrease after surgery. Important gait parameters for the discrimination were stride time and stride length. SIGNIFICANCE: The early identification of post-surgical functional outcomes of patients is of great importance to better inform patients pre-operatively regarding surgery success and to improve post-surgical management.


Assuntos
Artroplastia do Joelho/métodos , Análise da Marcha/métodos , Articulação do Joelho/fisiopatologia , Osteoartrite do Joelho/fisiopatologia , Acelerometria/métodos , Idoso , Feminino , Marcha/fisiologia , Humanos , Articulação do Joelho/cirurgia , Masculino , Pessoa de Meia-Idade , Osteoartrite do Joelho/cirurgia , Sensibilidade e Especificidade , Análise Espaço-Temporal , Resultado do Tratamento
16.
J Neurol ; 265(11): 2656-2665, 2018 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-30196324

RESUMO

Mobile, sensor-based gait analysis in Parkinson's disease (PD) facilitates the objective measurement of gait parameters in cross-sectional studies. Besides becoming outcome measures for clinical studies, the application of gait parameters in personalized clinical decision support is limited. Therefore, the aim of this study was to evaluate whether the individual response of PD patients to dopaminergic treatment may be measured by sensor-based gait analysis. 13 PD patients received apomorphine every 15 min to incrementally increase the bioavailable apomorphine dose. Motor performance (UPDRS III) was assessed 10 min after each apomorphine injection. Gait parameters were obtained after each UPDRS III rating from a 2 × 10 m gait sequence, providing 41.2 ± 9.2 strides per patient and injection. Gait parameters and UPDRS III ratings were compared cross-sectionally after apomorphine titration, and more importantly between consecutive injections for each patient individually. For the individual response, the effect size Cohen's d for gait parameter changes was calculated based on the stride variations of each gait sequence after each injection. Cross-sectionally, apomorphine improved stride speed, length, gait velocity, maximum toe clearance, and toe off angle. Between injections, the effect size for individual changes in stride speed, length, and maximum toe clearance correlated to the motor improvement in each patient. In addition, significant changes of stride length between injections were significantly associated with UPDRS III improvements. We therefore show, that sensor-based gait analysis provides objective gait parameters that support clinical assessment of individual PD patients during dopaminergic treatment. We propose clinically relevant instrumented gait parameters for treatment studies and especially clinical care.


Assuntos
Antiparasitários/uso terapêutico , Apomorfina/uso terapêutico , Agonistas de Dopamina/uso terapêutico , Análise da Marcha , Doença de Parkinson/tratamento farmacológico , Idoso , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Doença de Parkinson/fisiopatologia , Medicina de Precisão , Resultado do Tratamento
17.
Brain Behav ; 8(6): e00977, 2018 06.
Artigo em Inglês | MEDLINE | ID: mdl-29733529

RESUMO

BACKGROUND AND OBJECTIVES: Gait impairment and reduced mobility are typical features of idiopathic Parkinson's disease (iPD) and atypical parkinsonian disorders (APD). Quantitative gait assessment may have value in the diagnostic workup of parkinsonian patients and as endpoint in clinical trials. The study aimed to identify quantitative gait parameter differences in iPD and APD patients using sensor-based gait analysis and to correlate gait parameters with clinical rating scales. SUBJECTS AND METHODS: Patients with iPD and APD including Parkinson variant multiple system atrophy and progressive supranuclear palsy matched for age, gender, and Hoehn and Yahr (≤3) were recruited at two Movement Disorder Units and assessed using standardized clinical rating scales (MDS-UPDRS-3, UMSARS, PSP-RS). Gait analysis consisted of inertial sensor units laterally attached to shoes, generating as objective targets spatiotemporal gait parameters from 4 × 10 m walk tests. RESULTS: Objective sensor-based gait analysis showed that gait speed and stride length were markedly reduced in APD compared to iPD patients. Moreover, clinical ratings significantly correlated with gait speed and stride length in APD patients. CONCLUSION: Our findings suggest that patients with APD had more severely impaired gait parameters than iPD patients despite similar disease severity. Instrumented gait analysis provides complementary rater independent, quantitative parameters that can be exploited for clinical trials and care.


Assuntos
Análise da Marcha , Doença de Parkinson , Transtornos Parkinsonianos , Velocidade de Caminhada , Idoso , Estudos Transversais , Equipamentos para Diagnóstico , Progressão da Doença , Feminino , Análise da Marcha/instrumentação , Análise da Marcha/métodos , Humanos , Masculino , Pessoa de Meia-Idade , Atrofia de Múltiplos Sistemas/diagnóstico , Doença de Parkinson/diagnóstico , Doença de Parkinson/fisiopatologia , Transtornos Parkinsonianos/diagnóstico , Transtornos Parkinsonianos/fisiopatologia , Índice de Gravidade de Doença , Paralisia Supranuclear Progressiva/diagnóstico
18.
Sensors (Basel) ; 18(1)2018 Jan 06.
Artigo em Inglês | MEDLINE | ID: mdl-29316636

RESUMO

Robust gait segmentation is the basis for mobile gait analysis. A range of methods have been applied and evaluated for gait segmentation of healthy and pathological gait bouts. However, a unified evaluation of gait segmentation methods in Parkinson's disease (PD) is missing. In this paper, we compare four prevalent gait segmentation methods in order to reveal their strengths and drawbacks in gait processing. We considered peak detection from event-based methods, two variations of dynamic time warping from template matching methods, and hierarchical hidden Markov models (hHMMs) from machine learning methods. To evaluate the methods, we included two supervised and instrumented gait tests that are widely used in the examination of Parkinsonian gait. In the first experiment, a sequence of strides from instructed straight walks was measured from 10 PD patients. In the second experiment, a more heterogeneous assessment paradigm was used from an additional 34 PD patients, including straight walks and turning strides as well as non-stride movements. The goal of the latter experiment was to evaluate the methods in challenging situations including turning strides and non-stride movements. Results showed no significant difference between the methods for the first scenario, in which all methods achieved an almost 100% accuracy in terms of F-score. Hence, we concluded that in the case of a predefined and homogeneous sequence of strides, all methods can be applied equally. However, in the second experiment the difference between methods became evident, with the hHMM obtaining a 96% F-score and significantly outperforming the other methods. The hHMM also proved promising in distinguishing between strides and non-stride movements, which is critical for clinical gait analysis. Our results indicate that both the instrumented test procedure and the required stride segmentation algorithm have to be selected adequately in order to support and complement classical clinical examination by sensor-based movement assessment.


Assuntos
Marcha , Algoritmos , Transtornos Neurológicos da Marcha , Humanos , Doença de Parkinson
19.
Front Neurol ; 8: 550, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29123499

RESUMO

Introduction: Cognitive and gait deficits are common symptoms in Parkinson's disease (PD). Motor-cognitive dual tasks (DTs) are used to explore the interplay between gait and cognition. However, it is unclear if DT gait performance is indicative for cognitive impairment. Therefore, the aim of this study was to investigate if cognitive deficits are reflected by DT costs of spatiotemporal gait parameters. Methods: Cognitive function, single task (ST) and DT gait performance were investigated in 67 PD patients. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) followed by a standardized, sensor-based gait test and the identical gait test while subtracting serial 3's. Cognitive impairment was defined by a MoCA score <26. DT costs in gait parameters [(DT - ST)/ST × 100] were calculated as a measure of DT effect on gait. Correlation analysis was used to evaluate the association between MoCA performance and gait parameters. In a linear regression model, DT gait costs and clinical confounders (age, gender, disease duration, motor impairment, medication, and depression) were correlated to cognitive performance. In a subgroup analysis, we compared matched groups of cognitively impaired and unimpaired PD patients regarding differences in ST, DT, and DT gait costs. Results: Correlation analysis revealed weak correlations between MoCA score and DT costs of gait parameters (r/rSp ≤ 0.3). DT costs of stride length, swing time variability, and maximum toe clearance (|r/rSp| > 0.2) were included in a regression analysis. The parameters only explain 8% of the cognitive variance. In combination with clinical confounders, regression analysis showed that these gait parameters explained 30% of MoCA performance. Group comparison revealed strong DT effects within both groups (large effect sizes), but significant between-group effects in DT gait costs were not observed. Conclusion: These findings suggest that DT gait performance is not indicative for cognitive impairment in PD. DT effects on gait parameters were substantial in cognitively impaired and unimpaired patients, thereby potentially overlaying the effect of cognitive impairment on DT gait costs. Limits of the MoCA in detecting motor-function specific cognitive performance or variable individual response to the DT as influencing factors cannot be excluded. Therefore, DT gait parameters as marker for cognitive performance should be carefully interpreted in the clinical context.

20.
Conf Proc IEEE Eng Med Biol Soc ; 2017: 1266-1269, 2017 07.
Artigo em Inglês | MEDLINE | ID: mdl-29060107

RESUMO

Gait analysis is an important tool for diagnosis, monitoring and treatment of neurological diseases. Among these are hereditary spastic paraplegias (HSPs) whose main characteristic is heterogeneous gait disturbance. So far HSP gait has been analysed in a limited number of studies, and within a laboratory set up only. Although the rarity of orphan diseases often limits larger scale studies, the investigation of these diseases is still important, not only to the affect population, but also for other diseases which share gait characteristics.


Assuntos
Marcha , Paraplegia Espástica Hereditária
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