944 resultados para Gait cicle


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Aquest projecte es basa en una aplicació web per gestionar els costos de producció de granges o explotacions ramaderes de cicle tancat. El disseny i implementació l'he realitzat treballant a l'empresa Cooperativa Agropecuaria de Guissona. L'aplicació web està batejada amb el nom d'ECOPORC. Tot i ser una aplicació feta a mida per un tipus molt concret d'usuaris (els clients o socis de CAG), també es possible rebres usuaris no socis de l'empresa. Els llenguatges de programació utilitzats han esta: PHP, javascript, HTML. El servidor escollit ha estat l'Apache i la base de dades MySQL. L'aplicació web està sent utilitzada actualment per uns 30 usuaris i es preveu una evolució positiva.

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Es realitza un simulador de simulació discreta sobre el cicle de vida tancat en la producció de porcs. Per crear-lo s'utilitza el programa ExtendSim 6. Aquest simulador ens permet veure l'evolució durant cada etapa del cicle de vida del porc. D'aquí i de valors estadístics calculats es poden prendre decisions en la producció del porc. Per la seva realització s'ha creat uns blocs d'introducció i extracció de dades i uns de transició i engreix.

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OBJECTIVE: To investigate the association between fear of falling and gait performance in well-functioning older persons. DESIGN: Survey. SETTING: Community. PARTICIPANTS: Subjects (N=860, aged 65-70y) were a subsample of participants enrolled in a cohort study who underwent gait measurements. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Fear of falling and its severity were assessed by 2 questions about fear and related activity restriction. Gait performance, including gait variability, was measured using body-fixed sensors. RESULTS: Overall, 29.6% (210/860) of the participants reported fear of falling, with 5.2% (45/860) reporting activity restriction. Fear of falling was associated with reduced gait performance, including increased gait variability. A gradient in gait performance was observed from participants without fear to those reporting fear without activity restriction and those reporting both fear and activity restriction. For instance, stride velocity decreased from 1.15+/-.15 to 1.11+/-.17 to 1.00+/-.19 m/s (P<.001) in participants without fear, with fear but no activity restriction and with fear and activity restriction, respectively. In multivariate analysis, fear of falling with activity restriction remained associated with reduced gait performance, independent of sex, comorbidity, functional status, falls history, and depressive symptoms. CONCLUSIONS: In these well-functioning older people, those reporting fear of falling with activity restriction had reduced gait performance and increased gait variability, independent of health and functional status. These relationships suggest that early interventions targeting fear of falling might potentially help to prevent its adverse consequences on mobility and function in similar populations.

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Background: Mobile-bearing knee replacements have some theoretical advantages over fixed-bearing devices. However, very few randomized controlled clinical trials have been published to date, and studies showed little clinical and subjective advantages for the mobile-bearing using traditional systems of scoring. The choice of the ideal outcome measure to assess total joint replacement remains a complex issue. However, gait analysis provides objective and quantifying evidences of treatment evaluation. Significant methodological advances are currently made in gait analysis laboratories and ambulatory gait devices are now available. The goal of this study was to provide gait parameters as a new objective method to assess total knee arthroplasty outcome between patients with fixed- and mobile-bearing, using an ambulatory device with minimal sensor configuration. This randomized controlled double-blind study included to date 14 patients: the gait signatures of four patients with mobile-bearing were compared to the gait signatures of nine patients with fixed-bearing pre-operatively and post-operatively at 6 weeks, 3 months and 6 months. Each participant was asked to perform two walking trials of 30m long at his/her preferred speed and to complete a EQ-5D questionnaire, a WOMAC and Knee Society Score (KSS). Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. A new method for a portable system for gait analysis has been developed with very encouraging results regarding the objective outcome of total knee arthroplasty using mobile- and fixed-bearings.

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BACKGROUND: Complex foot and ankle fractures, such as calcaneum fractures or Lisfranc dislocations, are often associated with a poor outcome, especially in terms of gait capacity. Indeed, degenerative changes often lead to chronic pain and chronic functional limitations. Prescription footwear represents an important therapeutic tool during the rehabilitation process. Local Dynamic Stability (LDS) is the ability of locomotor system to maintain continuous walking by accommodating small perturbations that occur naturally during walking. Because it reflects the degree of control over the gait, LDS has been advocated as a relevant indicator for evaluating different conditions and pathologies. The aim of this study was to analyze changes in LDS induced by orthopaedic shoes in patients with persistent foot and ankle injuries. We hypothesised that footwear adaptation might help patients to improve gait control, which could lead to higher LDS: METHODS: Twenty-five middle-aged inpatients (5 females, 20 males) participated in the study. They were treated for chronic post-traumatic disabilities following ankle and/or foot fractures in a Swiss rehabilitation clinic. During their stay, included inpatients received orthopaedic shoes with custom-made orthoses (insoles). They performed two 30s walking trials with standard shoes and two 30s trials with orthopaedic shoes. A triaxial motion sensor recorded 3D accelerations at the lower back level. LDS was assessed by computing divergence exponents in the acceleration signals (maximal Lyapunov exponents). Pain was evaluated with Visual Analogue Scale (VAS). LDS and pain differences between the trials with standard shoes and the trials with orthopaedic shoes were assessed. RESULTS: Orthopaedic shoes significantly improved LDS in the three axes (medio-lateral: 10% relative change, paired t-test p < 0.001; vertical: 9%, p = 0.03; antero-posterior: 7%, p = 0.04). A significant decrease in pain level (VAS score -29%) was observed. CONCLUSIONS: Footwear adaptation led to pain relief and to improved foot & ankle proprioception. It is likely that that enhancement allows patients to better control foot placement. As a result, higher dynamic stability has been observed. LDS seems therefore a valuable index that could be used in early evaluation of footwear outcome in clinical settings.

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Time periods composing stance phase of gait can be clinically meaningful parameters to reveal differences between normal and pathological gait. This study aimed, first, to describe a novel method for detecting stance and inner-stance temporal events based on foot-worn inertial sensors; second, to extract and validate relevant metrics from those events; and third, to investigate their suitability as clinical outcome for gait evaluations. 42 subjects including healthy subjects and patients before and after surgical treatments for ankle osteoarthritis performed 50-m walking trials while wearing foot-worn inertial sensors and pressure insoles as a reference system. Several hypotheses were evaluated to detect heel-strike, toe-strike, heel-off, and toe-off based on kinematic features. Detected events were compared with the reference system on 3193 gait cycles and showed good accuracy and precision. Absolute and relative stance periods, namely loading response, foot-flat, and push-off were then estimated, validated, and compared statistically between populations. Besides significant differences observed in stance duration, the analysis revealed differing tendencies with notably a shorter foot-flat in healthy subjects. The result indicated which features in inertial sensors' signals should be preferred for detecting precisely and accurately temporal events against a reference standard. The system is suitable for clinical evaluations and provides temporal analysis of gait beyond the common swing/stance decomposition, through a quantitative estimation of inner-stance phases such as foot-flat.

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During free walking, gait is automatically adjusted to provide optimal mechanical output and minimal energy expenditure; gait parameters, such as cadence, fluctuate from one stride to the next around average values. It was described that this fluctuation exhibited long-range correlations and fractal-like patterns. In addition, it was suggested that these long-range correlations disappeared if the participant followed the beep of metronome to regulate his or her pace. Until now, these fractal fluctuations were only observed for stride interval, because no technique existed to adequately analyze an extended time of free walking. The aim of the present study was to measure walking speed (WS), step frequency (SF) and step length (SL) with high accuracy (<1 cm) satellite positioning method (global positioning system or GPS) in order to detect long-range correlations in the stride-to-stride fluctuations. Eight participants walked 30 min under free and constrained (metronome) conditions. Under free walking conditions, DFA (detrended fluctuation analysis) and surrogate data tests showed that the fluctuation of WS, SL and SF exhibited a fractal pattern (i.e., scaling exponent alpha: 0.5 < alpha < 1) in a large majority of participants (7/8). Under constrained conditions (metronome), SF fluctuations became significantly anti-correlated (alpha < 0.5) in all participants. However, the scaling exponent of SL and WS was not modified. We conclude that, when the walking pace is controlled by an auditory signal, the feedback loop between the planned movement (at supraspinal level) and the sensory inputs induces a continual shifting of SF around the mean (persistent anti-correlation), but with no effect on the fluctuation dynamics of the other parameters (SL, WS).

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Over the last century, numerous techniques have been developed to analyze the movement of humans while walking and running. The combined use of kinematics and kinetics methods, mainly based on high speed video analysis and forceplate, have permitted a comprehensive description of locomotion process in terms of energetics and biomechanics. While the different phases of a single gait cycle are well understood, there is an increasing interest to know how the neuro-motor system controls gait form stride to stride. Indeed, it was observed that neurodegenerative diseases and aging could impact gait stability and gait parameters steadiness. From both clinical and fundamental research perspectives, there is therefore a need to develop techniques to accurately track gait parameters stride-by-stride over a long period with minimal constraints to patients. In this context, high accuracy satellite positioning can provide an alternative tool to monitor outdoor walking. Indeed, the high-end GPS receivers provide centimeter accuracy positioning with 5-20 Hz sampling rate: this allows the stride-by-stride assessment of a number of basic gait parameters--such as walking speed, step length and step frequency--that can be tracked over several thousand consecutive strides in free-living conditions. Furthermore, long-range correlations and fractal-like pattern was observed in those time series. As compared to other classical methods, GPS seems a promising technology in the field of gait variability analysis. However, relative high complexity and expensiveness--combined with a usability which requires further improvement--remain obstacles to the full development of the GPS technology in human applications.

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Introduction: The SMILING project, a multicentric project fundedby the European Union, aims to develop a new gait and balance trainingprogram to prevent falls in older persons. The program includes the"SMILING shoe", an innovative device that generates mechanical perturbationwhile walking by changing the soles' inclination. Induced perturbationschallenge subjects' balance and force them to react to avoidfalls. By training specifically the complex motor reactions used to maintainbalance when walking on irregular ground, the program will improvesubjects' ability to react in situation of unsteadiness and reduce theirrisk of falling. Methods: The program will be evaluated in a multicentric,cross-over randomized controlled trial. Overall, 112 subjects (aged≥65 years, ≥1 falls, POMA score 22-26/28) will be enrolled. Subjectswill be randomised in 2 groups: group A begin the training with active"SMILING shoes", group B with inactive dummy shoes. After 4 weeksof training, group A and B will exchange the shoes. Supervised trainingsessions (30 minutes twice a week for 8 weeks) include walkingtasks of progressive difficulties.To avoid a learning effect, "SMILINGshoes" perturbations will be generated in a non-linear and chaotic way.Gait performance, fear of falling, and acceptability of the program willbe assessed. Conclusion: The SMILING program is an innovative interventionfor falls prevention in older persons based on gait and balancetraining using chaotic perturbations. Because of the easy use of the"SMILING shoes", this program could be used in various settings, suchas geriatric clinics or at home.

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BACKGROUND: The use of robots for gait training in Parkinson disease (PD) is growing, but no evidence points to an advantage over the standard treadmill. METHODS: In this randomized, single-blind controlled trial, participants aged <75 years with early-stage PD (Hoehn-Yahr <3) were randomly allocated to 2 groups: either 30 minutes of gait training on a treadmill or in the Lokomat for 3 d/wk for 4 weeks. Patients were evaluated by a physical therapist blinded to allocation before and at the end of treatment and then at the 3- and 6-month follow-up. The primary outcome measure was the 6-minute walk test. RESULTS: Of 334 screened patients, the authors randomly allocated 30 to receive gait training with treadmill or the Lokomat. At baseline, the 2 groups did not differ. At the 6-month follow-up, both groups had improved significantly in the primary outcome measure (treadmill: mean = 490.95 m, 95% confidence interval [CI] = 448.56-533.34, P = .0006; Lokomat: 458.6 m, 95% CI = 417.23-499.96, P = .01), but no significant differences were found between the 2 groups (P = .53). DISCUSSION: Robotic gait training with the Lokomat is not superior to treadmill training in improving gait performance in patients with PD. Both approaches are safe, with results maintained for up to 6 months.

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Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

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Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ± 3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects.