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1.
Licere (Online) ; 24(02): 624-665, 20210630. ilus
Artigo em Português | LILACS | ID: biblio-1291517

RESUMO

Neste artigo serão abordadas algumas questões relativas às mudanças na razão e na sensibilidade do trato do ser humano com o mundo natural e que possam fornecer alguns indícios do apreço que os indivíduos, na atualidade, têm acerca de realizaram caminhadas pelo campo, considerando os séculos XVIII e XIX como ápice desse processo de transformação da mentalidade.


In this article, some issues related to changes in the reason and sensitivity of the human being's treatment with the natural world will be approached, which may provide some indications of the appreciation that individuals, at present, have about undertaking walks in the countryside, considering the 18th and 19th centuries as the culmination of this mentality transformation process.


Assuntos
Caminhada
2.
Rev Bras Enferm ; 75(2): e20210128, 2021.
Artigo em Inglês, Português | MEDLINE | ID: mdl-34614104

RESUMO

OBJECTIVE: to describe the profile of nursing diagnoses evidenced in indigenous elderly in the community. METHODS: this is a cross-sectional study, carried out with 51 indigenous elderly people of Potiguara ethnicity, through a nursing consultation. The clinical data, obtained from the consultation, were analyzed following Risner's diagnostic reasoning process and the NANDA-I Taxonomy (2018-2020). For greater accuracy, the diagnoses obtained underwent peer review by a specialist. RESULTS: 37 diagnoses were identified, such as Impaired dentition (98.0%), Risk for impaired skin integrity (66.7%), Chronic pain (64.7%), Risk for deficient fluid volume (54.9%), Impaired swallowing (45.1%), Impaired walking (45.1%), Disturbed sleep pattern (43.1%), Stress urinary incontinence (41.2%), Risk for falls (35.3%), and Sexual dysfunction (33.3%). CONCLUSION: the diagnoses identified were predominantly from Safety/protection domain and result from factors that negatively influence indigenous elderly's functional capacity.


Assuntos
Diagnóstico de Enfermagem , Caminhada , Idoso , Estudos Transversais , Humanos
3.
MMWR Morb Mortal Wkly Rep ; 70(40): 1408-1414, 2021 Oct 08.
Artigo em Inglês | MEDLINE | ID: mdl-34618794

RESUMO

The numerous health benefits of physical activity include reduced risk for chronic disease and improved mental health and quality of life (1). Physical activity can improve physical function and reduce pain and fall risk among adults with arthritis, a group of approximately 100 conditions affecting joints and surrounding tissues (most commonly osteoarthritis, fibromyalgia, gout, rheumatoid arthritis, and lupus) (1). Despite these benefits, the 54.6 million U.S. adults currently living with arthritis are generally less active than adults without arthritis, and only 36.2% of adults with arthritis are aerobically active (i.e., meet aerobic physical activity guidelines*) (2). Little is known about which physical activities adults with arthritis engage in. CDC analyzed 2019 Behavioral Risk Factor Surveillance System (BRFSS) data to examine the most common nonwork-related physical activities among adults with arthritis who reported any physical activity during the past month, nationally and by state. In 2019, 67.2% of adults with arthritis reported engaging in physical activity in the past month; among these persons, the most commonly reported activities were walking (70.8%), gardening (13.3%), and weightlifting (7.3%). In 45 U.S. states, at least two thirds of adults with arthritis who engaged in physical activity reported walking. Health care providers can help inactive adults with arthritis become active and, by encouraging physical activity and referring these persons to evidence-based physical activity programs, improve their health and quality of life.


Assuntos
Artrite/epidemiologia , Exercício Físico , Caminhada/estatística & dados numéricos , Adolescente , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estados Unidos/epidemiologia , Adulto Jovem
4.
BMJ Case Rep ; 14(10)2021 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-34610956

RESUMO

A 23-year-old female-treated patient of osteomalacia and secondary hyperparathyroidism with hypophosphatemia presented with a 5-year history of bilateral groin pain and stiffness of both hips and difficulty in walking. Plain radiographs of the pelvis showed bilateral coxa vara deformity. She was managed surgically by a single-stage bilateral subtrochanteric corrective osteotomy with the internal fixation. After the osteotomy healing at 3 months, the patient was pain free and walked comfortably with an increased range of hip motion.


Assuntos
Coxa Vara , Adulto , Coxa Vara/diagnóstico por imagem , Feminino , Fixação Interna de Fraturas , Humanos , Osteotomia , Radiografia , Caminhada , Adulto Jovem
5.
Sensors (Basel) ; 21(19)2021 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-34640686

RESUMO

Quadruped robots are receiving great attention as a new means of transportation for various purposes, such as military, welfare, and rehabilitation systems. The use of four legs enables a robustly stable gait; compared to the humanoid robots, the quadruped robots are particularly advantageous in improving the locomotion speed, the maximum payload, and the robustness toward disturbances. However, the more demanding conditions robots are exposed to, the more challenging the trajectory generation of robotic legs becomes. Although various trajectory generation methods (e.x., central pattern generator, finite states machine) have been developed for this purpose, these methods have limited degrees of freedom with respect to the gait transition. The conventional methods do not consider the transition of the gait phase (i.e., walk, amble, trot, canter, and gallop) or use a pre-determined fixed gait phase. Additionally, some research teams have developed locomotion algorithms that take into account the transition of the gait phase. Still, the transition of the gait phase is limited (mostly from walking to trot), and the transition according to gait speed is not considered. In this paper, a multi-phase joint-angle trajectory generation algorithm is proposed for the quadruped robot. The joint-angles of an animal are expressed as a cyclic basis function, and an input to the basis function is manipulated to realize the joint-angle trajectories in multiple gait phases as desired. To control the desired input of a cyclic basis function, a synchronization function is formulated, by which the motions of legs are designed to have proper ground contact sequences with each other. In the gait of animals, each gait phase is optimal for a certain speed, and thus transition of the gait phases is necessary for effective increase or decrease in the locomotion speed. The classification of the gait phases, however, is discrete, and thus the resultant joint-angle trajectories may be discontinuous due to the transition. For the smooth and continuous transition of gait phases, fuzzy logic is utilized in the proposed algorithm. The proposed methods are verified by simulation studies.


Assuntos
Robótica , Animais , Cães , Marcha , Locomoção , Movimento (Física) , Caminhada
6.
Sensors (Basel) ; 21(19)2021 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-34640712

RESUMO

Generally, people do various things while walking. For example, people frequently walk while looking at their smartphones. Sometimes we walk differently than usual; for example, when walking on ice or snow, we tend to waddle. Understanding walking patterns could provide users with contextual information tailored to the current situation. To formulate this as a machine-learning problem, we defined 18 different everyday walking styles. Noting that walking strategies significantly affect the spatiotemporal features of hand motions, e.g., the speed and intensity of the swinging arm, we propose a smartwatch-based wearable system that can recognize these predefined walking styles. We developed a wearable system, suitable for use with a commercial smartwatch, that can capture hand motions in the form of multivariate timeseries (MTS) signals. Then, we employed a set of machine learning algorithms, including feature-based and recent deep learning algorithms, to learn the MTS data in a supervised fashion. Experimental results demonstrated that, with recent deep learning algorithms, the proposed approach successfully recognized a variety of walking patterns, using the smartwatch measurements. We analyzed the results with recent attention-based recurrent neural networks to understand the relative contributions of the MTS signals in the classification process.


Assuntos
Redes Neurais de Computação , Caminhada , Algoritmos , Humanos , Aprendizado de Máquina
7.
Sensors (Basel) ; 21(19)2021 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-34640722

RESUMO

Physical exercise contributes to the success of rehabilitation programs and rehabilitation processes assisted through social robots. However, the amount and intensity of exercise needed to obtain positive results are unknown. Several considerations must be kept in mind for its implementation in rehabilitation, as monitoring of patients' intensity, which is essential to avoid extreme fatigue conditions, may cause physical and physiological complications. The use of machine learning models has been implemented in fatigue management, but is limited in practice due to the lack of understanding of how an individual's performance deteriorates with fatigue; this can vary based on physical exercise, environment, and the individual's characteristics. As a first step, this paper lays the foundation for a data analytic approach to managing fatigue in walking tasks. The proposed framework establishes the criteria for a feature and machine learning algorithm selection for fatigue management, classifying four fatigue diagnoses states. Based on the proposed framework and the classifier implemented, the random forest model presented the best performance with an average accuracy of ≥98% and F-score of ≥93%. This model was comprised of ≤16 features. In addition, the prediction performance was analyzed by limiting the sensors used from four IMUs to two or even one IMU with an overall performance of ≥88%.


Assuntos
Caminhada , Dispositivos Eletrônicos Vestíveis , Algoritmos , Fadiga/diagnóstico , Humanos , Aprendizado de Máquina
8.
Sensors (Basel) ; 21(19)2021 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-34640743

RESUMO

BACKGROUND: The objective gait assessment in children has become more popular. Basis parameters for comparison during the examination are advisable. OBJECTIVES: The study aim was to investigate the typical gait parameters of healthy preschool and school children, using a wireless inertial sensor as the reference for atypical gait. The additional aim was to compare the specific gait parameters in the younger and older group of children. METHODS: One hundred and sixty-one children's gait parameters were evaluated by a G-Walk BTS G-SENSOR smart analyzer. The children were walking barefoot, at a self-selected speed, on a five-meter walkway, and they turned around and go back twice. RESULTS: Age significantly influences most of the spatiotemporal parameters. The support phase becomes shorter with age. Accordingly, the swing phase becomes longer with age. The results also show that older children need shorter double support and have longer single support. Moreover, the pelvic tilt symmetry index is higher with increasing age. In each age division, the smallest variation in all gait parameters within the oldest group of examined children was observed. A comparison between the left and right side gait parameters shows the higher difference in boys than in girls. A significant difference was calculated in the pelvic obliquity symmetry index. Girls had significantly more symmetrical obliquity than boys. CONCLUSIONS: the research indicates the basic parameters of typical children's gait, which may be a reference to atypical gait in the case of trauma or disability.


Assuntos
Marcha , Caminhada , Adolescente , Criança , Pré-Escolar , Feminino , Nível de Saúde , Humanos , Masculino , Instituições Acadêmicas
9.
Sensors (Basel) ; 21(19)2021 Sep 27.
Artigo em Inglês | MEDLINE | ID: mdl-34640771

RESUMO

Normal pressure hydrocephalus (NPH) is a chronic and progressive disease that affects predominantly elderly subjects. The most prevalent symptoms are gait disorders, generally determined by visual observation or measurements taken in complex laboratory environments. However, controlled testing environments can have a significant influence on the way subjects walk and hinder the identification of natural walking characteristics. The study aimed to investigate the differences in walking patterns between a controlled environment (10 m walking test) and real-world environment (72 h recording) based on measurements taken via a wearable gait assessment device. We tested whether real-world environment measurements can be beneficial for the identification of gait disorders by performing a comparison of patients' gait parameters with an aged-matched control group in both environments. Subsequently, we implemented four machine learning classifiers to inspect the individual strides' profiles. Our results on twenty young subjects, twenty elderly subjects and twelve NPH patients indicate that patients exhibited a considerable difference between the two environments, in particular gait speed (p-value p=0.0073), stride length (p-value p=0.0073), foot clearance (p-value p=0.0117) and swing/stance ratio (p-value p=0.0098). Importantly, measurements taken in real-world environments yield a better discrimination of NPH patients compared to the controlled setting. Finally, the use of stride classifiers provides promise in the identification of strides affected by motion disorders.


Assuntos
Transtornos Neurológicos da Marcha , Hidrocefalia de Pressão Normal , Idoso , , Marcha , Transtornos Neurológicos da Marcha/diagnóstico , Humanos , Caminhada
10.
Sensors (Basel) ; 21(19)2021 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-34640799

RESUMO

Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson's Disease, PD) and/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 × lower back and 1 × shin/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.


Assuntos
Doença de Parkinson , Dispositivos Eletrônicos Vestíveis , Idoso , Algoritmos , Marcha , Humanos , Doença de Parkinson/diagnóstico , Caminhada , Adulto Jovem
11.
Sensors (Basel) ; 21(19)2021 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-34640838

RESUMO

Walking has been demonstrated to improve health in people with diabetes and peripheral arterial disease. However, continuous walking can produce repeated stress on the plantar foot and cause a high risk of foot ulcers. In addition, a higher walking intensity (i.e., including different speeds and durations) will increase the risk. Therefore, quantifying the walking intensity is essential for rehabilitation interventions to indicate suitable walking exercise. This study proposed a machine learning model to classify the walking speed and duration using plantar region pressure images. A wearable plantar pressure measurement system was used to measure plantar pressures during walking. An Artificial Neural Network (ANN) was adopted to develop a model for walking intensity classification using different plantar region pressure images, including the first toe (T1), the first metatarsal head (M1), the second metatarsal head (M2), and the heel (HL). The classification consisted of three walking speeds (i.e., slow at 0.8 m/s, moderate at 1.6 m/s, and fast at 2.4 m/s) and two walking durations (i.e., 10 min and 20 min). Of the 12 participants, 10 participants (720 images) were randomly selected to train the classification model, and 2 participants (144 images) were utilized to evaluate the model performance. Experimental evaluation indicated that the ANN model effectively classified different walking speeds and durations based on the plantar region pressure images. Each plantar region pressure image (i.e., T1, M1, M2, and HL) generates different accuracies of the classification model. Higher performance was achieved when classifying walking speeds (0.8 m/s, 1.6 m/s, and 2.4 m/s) and 10 min walking duration in the T1 region, evidenced by an F1-score of 0.94. The dataset T1 could be an essential variable in machine learning to classify the walking intensity at different speeds and durations.


Assuntos
Caminhada , Dispositivos Eletrônicos Vestíveis , , Humanos , Redes Neurais de Computação , Pressão
12.
Sensors (Basel) ; 21(19)2021 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-34640862

RESUMO

Being able to capture relevant information about elite athletes' movement "in the wild" is challenging, especially because reference marker-based approaches hinder natural movement and are highly sensitive to environmental conditions. We propose Pose2Sim, a markerless kinematics workflow that uses OpenPose 2D pose detections from multiple views as inputs, identifies the person of interest, robustly triangulates joint coordinates from calibrated cameras, and feeds those to a 3D inverse kinematic full-body OpenSim model in order to compute biomechanically congruent joint angles. We assessed the robustness of this workflow when facing simulated challenging conditions: (Im) degrades image quality (11-pixel Gaussian blur and 0.5 gamma compression); (4c) uses few cameras (4 vs. 8); and (Cal) introduces calibration errors (1 cm vs. perfect calibration). Three physical activities were investigated: walking, running, and cycling. When averaged over all joint angles, stride-to-stride standard deviations lay between 1.7° and 3.2° for all conditions and tasks, and mean absolute errors (compared to the reference condition-Ref) ranged between 0.35° and 1.6°. For walking, errors in the sagittal plane were: 1.5°, 0.90°, 0.19° for (Im), (4c), and (Cal), respectively. In conclusion, Pose2Sim provides a simple and robust markerless kinematics analysis from a network of calibrated cameras.


Assuntos
Corrida , Caminhada , Fenômenos Biomecânicos , Humanos , Movimento , Fluxo de Trabalho
13.
Sensors (Basel) ; 21(19)2021 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-34640875

RESUMO

Frailty and falls are a major public health problem in older adults. Muscle weakness of the lower and upper extremities are risk factors for any, as well as recurrent falls including injuries and fractures. While the Timed Up-and-Go (TUG) test is often used to identify frail members and fallers, tensiomyography (TMG) can be used as a non-invasive tool to assess the function of skeletal muscles. In a clinical study, we evaluated the correlation between the TMG parameters of the skeletal muscle contraction of 23 elderly participants (22 f, age 86.74 ± 7.88) and distance-based TUG test subtask times. TUG tests were recorded with an ultrasonic-based device. The sit-up and walking phases were significantly correlated to the contraction and delay time of the muscle vastus medialis (ρ = 0.55-0.80, p < 0.01). In addition, the delay time of the muscles vastus medialis (ρ = 0.45, p = 0.03) and gastrocnemius medialis (ρ = -0.44, p = 0.04) correlated to the sit-down phase. The maximal radial displacements of the biceps femoris showed significant correlations with the walk-forward times (ρ = -0.47, p = 0.021) and back (ρ = -0.43, p = 0.04). The association of TUG subtasks to muscle contractile parameters, therefore, could be utilized as a measure to improve the monitoring of elderly people's physical ability in general and during rehabilitation after a fall in particular. TUG test subtask measurements may be used as a proxy to monitor muscle properties in rehabilitation after long hospital stays and injuries or for fall prevention.


Assuntos
Fragilidade , Contração Muscular , Idoso , Idoso de 80 Anos ou mais , Humanos , Músculo Esquelético , Músculo Quadríceps , Caminhada
14.
Sensors (Basel) ; 21(19)2021 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-34640878

RESUMO

Climbing stairs is a fundamental part of daily life, adding additional demands on the postural control system compared to level walking. Although real-world gait analysis studies likely contain stair ambulation sequences, algorithms dedicated to the analysis of such activities are still missing. Therefore, we propose a new gait analysis pipeline for foot-worn inertial sensors, which can segment, parametrize, and classify strides from continuous gait sequences that include level walking, stair ascending, and stair descending. For segmentation, an existing approach based on the hidden Markov model and a feature-based gait event detection were extended, reaching an average segmentation F1 score of 98.5% and gait event timing errors below ±10ms for all conditions. Stride types were classified with an accuracy of 98.2% using spatial features derived from a Kalman filter-based trajectory reconstruction. The evaluation was performed on a dataset of 20 healthy participants walking on three different staircases at different speeds. The entire pipeline was additionally validated end-to-end on an independent dataset of 13 Parkinson's disease patients. The presented work aims to extend real-world gait analysis by including stair ambulation parameters in order to gain new insights into mobility impairments that can be linked to clinically relevant conditions such as a patient's fall risk and disease state or progression.


Assuntos
Análise da Marcha , Caminhada , Algoritmos , , Marcha , Humanos
15.
Sensors (Basel) ; 21(19)2021 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-34640938

RESUMO

This paper introduces a new device for gait rehabilitation, the gait propulsion trainer (GPT). It consists of two main components (a stationary device and a wearable system) that work together to apply periodic stance-phase resistance as the user walks overground. The stationary device provides the resistance forces via a cable that tethers the user's pelvis to a magnetic-particle brake. The wearable system detects gait events via foot switches to control the timing of the resistance forces. A hardware verification test confirmed that the GPT functions as intended. We conducted a pilot study in which one healthy adult and one stroke survivor walked with the GPT with increasing resistance levels. As hypothesized, the periodic stance-phase resistance caused the healthy participant to walk asymmetrically, with greatly reduced propulsion impulse symmetry; as GPT resistance increased, the walking speed also decreased, and the propulsion impulse appeared to increase for both legs. In contrast, the stroke participant responded to GPT resistance by walking faster and more symmetrically in terms of both propulsion impulse and step length. Thus, this paper shows promising results of short-term training with the GPT, and more studies will follow to explore its long-term effects on hemiparetic gait.


Assuntos
Transtornos Neurológicos da Marcha , Reabilitação do Acidente Vascular Cerebral , Adulto , Marcha , Humanos , Projetos Piloto , Caminhada
16.
Sensors (Basel) ; 21(19)2021 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-34640945

RESUMO

Gait symmetry analysis plays an important role in the diagnosis and rehabilitation of pathological gait. Recently, wearable devices have also been developed for simple gait analysis solutions. However, measurement in clinical settings can differ from gait in daily life, and simple wearable devices are restricted to a few parameters, providing one-sided trajectories of one arm or leg. Therefore, head-worn devices with sensors (e.g., earbuds) should be considered to analyze gait symmetry because the head sways towards the left and right side depending on steps. This paper proposed new visualization methods using head-worn sensors, able to facilitate gait symmetry analysis outside as well as inside. Data were collected with an inertial measurement unit (IMU) based motion capture system when twelve participants walked on the 400-m running track. From head trajectories on the transverse and frontal plane, three types of diagrams were displayed, and five concepts of parameters were measured for gait symmetry analysis. The mean absolute percentage error (MAPE) of step counting was lower than 0.65%, representing the reliability of measured parameters. The methods enable also left-right step recognition (MAPE ≤ 2.13%). This study can support maintenance and relearning of a balanced healthy gait in various areas with simple and easy-to-use devices.


Assuntos
Análise da Marcha , Caminhada , Marcha , Cabeça , Humanos , Reprodutibilidade dos Testes
17.
Sensors (Basel) ; 21(19)2021 Oct 06.
Artigo em Inglês | MEDLINE | ID: mdl-34640956

RESUMO

Stumbling during gait is commonly encountered in patients who suffer from mild to serious walking problems, e.g., after stroke, in osteoarthritis, or amputees using a lower leg prosthesis. Instead of self-reporting, an objective assessment of the number of stumbles in daily life would inform clinicians more accurately and enable the evaluation of treatments that aim to achieve a safer walking pattern. An easy-to-use wearable might fulfill this need. The goal of the present study was to investigate whether a single inertial measurement unit (IMU) placed at the shank and machine learning algorithms could be used to detect and classify stumbling events in a dataset comprising of a wide variety of daily movements. Ten healthy test subjects were deliberately tripped by an unexpected and unseen obstacle while walking on a treadmill. The subjects stumbled a total of 276 times, both using an elevating recovery strategy and a lowering recovery strategy. Subjects also performed multiple Activities of Daily Living. During data processing, an event-defined window segmentation technique was used to trace high peaks in acceleration that could potentially be stumbles. In the reduced dataset, time windows were labelled with the aid of video annotation. Subsequently, discriminative features were extracted and fed to train seven different types of machine learning algorithms. Trained machine learning algorithms were validated using leave-one-subject-out cross-validation. Support Vector Machine (SVM) algorithms were most successful, and could detect and classify stumbles with 100% sensitivity, 100% specificity, and 96.7% accuracy in the independent testing dataset. The SVM algorithms were implemented in a user-friendly, freely available, stumble detection app named Stumblemeter. This work shows that stumble detection and classification based on SVM is accurate and ready to apply in clinical practice.


Assuntos
Atividades Cotidianas , Membros Artificiais , Marcha , Humanos , Máquina de Vetores de Suporte , Caminhada
18.
Sensors (Basel) ; 21(19)2021 Oct 06.
Artigo em Inglês | MEDLINE | ID: mdl-34640963

RESUMO

Age-related mobility research often highlights significant mobility differences comparing neurotypical young and older adults, while neglecting to report mobility outcomes for middle-aged adults. Moreover, these analyses regularly do not determine which measures of mobility can discriminate groups into their age brackets. Thus, the current study aimed to provide a comprehensive analysis for commonly performed aspects of mobility (walking, turning, sit-to-stand, and balance) to determine which variables were significantly different and furthermore, able to discriminate between neurotypical young adults (YAs), middle-aged adults (MAAs), and older adults (OAs). This study recruited 20 YAs, 20 MAAs, and 20 OAs. Participants came into the laboratory and completed mobility testing while wearing wireless inertial sensors. Mobility tests assessed included three distinct two-minute walks, 360° turns, five times sit-to-stands, and a clinical balance test, capturing 99 distinct mobility metrics. Of the various mobility tests assessed, only 360° turning measures demonstrated significance between YAs and MAAs, although the capacity to discriminate between groups was achieved for gait and turning measures. A variety of mobility measures demonstrated significance between MAAs and OAs, and furthermore discrimination was achieved for each mobility test. These results indicate greater mobility differences between MAAs and OAs, although discrimination is achievable for both group comparisons.


Assuntos
Marcha , Caminhada , Idoso , Humanos , Pessoa de Meia-Idade , Adulto Jovem
19.
Ethiop J Health Sci ; 31(3): 505-516, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-34483607

RESUMO

Background: Efficacies of community-based exercise programmes have been well reported but there is scarce information on the expediency of community-based rehabilitation in a society where many of children with disabilities live in poorly resourced settings with extremely limited rehabilitative services. The study investigated the effects of community-based functional aerobic exercise (CBFAE) on gross motor function, walking distance, and quality of life of children with cerebral palsy (CP). Methods: Quasi-experimental design was used. Children with gross motor function classification system (GMFCS) levels I - II participated in eight weeks CBFAE training four times/week, 50 minutes/day at 40-80% maximum heart rate. Gross motor function (GMF), walk distance and quality of life were assessed pre and post CBFAE training. Results: Significant improvement observed in GMF (Dstanding) (8.2%, P=.000), GMF (E-walking+running+jumping (5.12%, P=.004), walking distance (6.09%, P=.009). Higher significant positive effects of CBFAE observed in Social wellbeing and acceptance (107.10%, P=.000), and participation and physical health (105.04%, P=.005) by children parent proxy. Self-reported results showed that for CBFAE, significant positive improvements were higher in Pain and impact of disability (67.93%, P=.049) and Participation and physical health (60.00%, P=.042). Conclusion: CBFAE training contributes majorly to improved standing, walking, jumping and running and selfesteem, quality of life of children with spastic CP. Clinicians and exercise therapists should essentially incorporate CBFAE training and activities into the management of children with CP for improved mobility and functional performances.


Assuntos
Paralisia Cerebral , Criança , Exercício Físico , Humanos , Qualidade de Vida , Caminhada
20.
Lakartidningen ; 1182021 Aug 24.
Artigo em Sueco | MEDLINE | ID: mdl-34498242

RESUMO

Foot drop (FD) can be caused by a variety of diseases and injuries. FD leads to walking difficulties and reduced balance which also can lead to a higher risk of falling. Patient with a stroke often have an equinovarus deformity of the foot together with the DF. There is a need to optimize and standardize the treatment for patients with FD across different medical specialities. Surgical interventions, with goals of producing a balanced functional foot, have been shown to improve the function and quality of life and decrease the use of braces and walking aids in patients with FD after a CVI. In Sweden data regarding FD surgery is collected in the National Quality Registry for Foot and Ankle Surgery (Riksfot), but there is also an ongoing multicentre study, investigating the patient-reported and functional results of surgery due to FD caused by a CVI.


Assuntos
Pé Torto Equinovaro , Procedimentos Ortopédicos , Neuropatias Fibulares , Reabilitação do Acidente Vascular Cerebral , Acidente Vascular Cerebral , Pé Torto Equinovaro/cirurgia , Humanos , Estudos Multicêntricos como Assunto , Qualidade de Vida , Acidente Vascular Cerebral/complicações , Caminhada
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