23 resultados para abduction
Resumo:
Background: In recent years, there have been investigations concerning upper-limbs kinematics by various devices. The latest generation of smartphones often includes inertial sensors with subunits which can detect inertial kinematics. The use of smartphones is presented as a convenient and portable analysis method for studying kinematics in terms of angular mobility and linear acceleration Objective: The aim of this study was to study humerus kinematics through six physical properties that correspond to angular mobility and acceleration in the three axes of space, obtained by a smartphone. Methods: This cross-sectional study recruited healthy young adult subjects. Descriptive and anthropometric independent variables related to age, gender, weight, size, and BMI were included. Six physical properties were included corresponding to two dependent variables for each of three special axes: mobility angle (degrees) and lineal acceleration (meters/seconds2), which were obtained thought the inertial measurement sensor embedded in the iPhone4 smartphone equipped with three two elements for the detection of kinematic variables: a gyroscope and an accelerometer. Apple uses an LIS302DL accelerometer in the iPhone4. The application used to obtain kinematic data was xSensor Pro, Crossbow Technology, Inc., available at the Apple AppStore. The iPhone4 has storage capacity of 20MB. The data-sampling rate was set to 32 Hz, and the data for each analytical task was transmitted as email for analysis and postprocessing The iPhone4 was placed in the right half of the body of each subject located in the middle third of the humerus slightly posterior snugly secured by a neoprene fixation belt. Tasks were explained concisely and clearly. The beginning and the end were decided by a verbal order by the researcher. Participants were placed standing, starting from neutral position, performing the following analytical tasks: 180º right shoulder abduction (eight repetitions) and, after a break of about 3 minutes, 180º right shoulder flexion (eight repetitions). Both tasks were performed with the elbow extended, wrist in neutral position and the palmar area of the hand toward the midline at the beginning and end of the movement. Results: A total of 11 subjects (8 men, 3 woman) were measured, whose mean of age was 24.7 years (SD = 4.22 years) and their average BMI was 22.64 Kg/m2 (SD = 2.29 Kg/m2). The mean of angular mobility collected by the smartphone was bigger in pitch axis for flexion (= 157.28°, SD= 12.35°) and abduction (= 151.71°, SD= 9.70°). With regard to acceleration, the highest peak mean value was shown in the Y motion axis during flexion (= 19.5°/s2, SD = 0.8°/s2) and abduction (= 19.4°/s2, SD = 0.8°/s2). Also, descriptive graphics of analytical tasks performed were obtained. Conclusions: This study shows how humerus contributes to upper-limb motion and it identified movement patterns. Therefore, it supports smartphone as a useful device to analyze upper-limb kinematics. Thanks to this study it´s possible to develop a simple application that facilitates the evaluation of the patient.
Resumo:
This presentation will provide an overview of the load applied on the residuum of transfemoral amputees fitted with an osseointegrated fixation during (A) rehabilitation, including static and dynamic load bearing exercises (e.g., rowing, adduction, abduction, squat, cycling, walking with aids), and (B) activities of daily living including standardized activities (e.g., level walking in straight line and around a circle, ascending and descending slopes and stairs) and activities in real world environments.
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Researchers have postulated that reduced hip-abductor muscle strength may have a role in the progression of knee osteoarthritis by increasing the external knee-adduction moment. However, the relationship between hip-abductor strength and frontal-plane biomechanics remains unclear. To experimentally reduce hip-abduction strength and observe the subsequent changes in frontal-plane biomechanics. Descriptive laboratory study. Research laboratory. Eight healthy, recreationally active men (age = 27 ± 6 years, height = 1.75 ± 0.11 m, mass = 76.1 ± 10.0 kg). All participants underwent a superior gluteal nerve block injection to reduce the force output of the hip-abductor muscle group. Maximal isometric hip-abduction strength and gait biomechanical data were collected before and after the injections. Gait biomechanical variables collected during walking consisted of knee- and hip-adduction moments and impulses and the peak angles of contralateral pelvic drop, hip adduction, and ipsilateral trunk lean. Hip-abduction strength was reduced after the injection (P = .001) and remained lower than baseline values at the completion of the postinjection gait data collection (P = .02). No alterations in hip- or knee-adduction moments (hip: P = .11; knee: P = .52) or impulses (hip: P = .16; knee: P = .41) were found after the nerve block. Similarly, no changes in angular kinematics were observed for contralateral pelvic drop (P = .53), ipsilateral trunk lean (P = .78), or hip adduction (P = .48). A short-term reduction in hip-abductor strength was not associated with alterations in the frontal-plane gait biomechanics of young, healthy men. Further research is needed to determine whether a similar relationship is true in older adults with knee osteoarthritis.
Resumo:
Objective The objectives of this cross-sectional, analytical inference analysis were to compare shoulder muscle activation at arm elevations of 0° to 90° through different movement planes and speeds during in-water and dry-land exercise and to extrapolate this information to a clinical rehabilitation model. Methods Six muscles of right-handed adult subjects (n = 16; males/females: 50%; age: 26.1 ± 4.5 years) were examined with surface electromyography during arm elevation in water and on dry land. Participants randomly performed 3 elevation movements (flexion, abduction, and scaption) through 0° to 90°. Three movement speeds were used for each movement as determined by a metronome (30°/sec, 45°/sec, and 90°/sec). Dry-land maximal voluntary contraction tests were used to determine movement normalization. Results Muscle activity levels were significantly lower in water compared with dry land at 30°/sec and 45°/sec but significantly higher at 90°/sec. This sequential progressive activation with increased movement speed was proportionally higher on transition from gravity-based on-land activity to water-based isokinetic resistance. The pectoralis major and latissimus dorsi muscles showed higher activity during abduction and scaption. Conclusions These findings on muscle activation suggest protocols in which active flexion is introduced first at low speeds (30°/sec) in water, then at medium speeds (45°/sec) in water or on dry land, and finally at high speeds (90°/sec) on dry land before in water. Abduction requires higher stabilization, necessitating its introduction after flexion, with scaption introduced last. This model of progressive sequential movement ensures that early active motion and then stabilization are appropriately introduced. This should reduce rehabilitation time and improve therapeutic goals without compromising patient safety or introducing inappropriate muscle recruitment or movement speed.
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Introduction Axillary web syndrome (AWS) can result in early post-operative and long-term difficulties following lymphadenectomy for cancer and should be recognised by clinicians. This systematic review was conducted to synthesise information on AWS clinical presentation and diagnosis, frequency, natural progression, grading, pathoaetiology, risk factors, symptoms, interventions and outcomes. Methods Electronic searches were conducted using Cochrane, Pubmed, MEDLINE, CINAHL, EMBASE, AMED, PEDro and Google Scholar until June 2013. The methodological quality of included studies was determined using the Downs and Black checklist. Narrative synthesis of results was undertaken. Results Thirty-seven studies with methodological quality scores ranging from 11 to 26 on a 28-point scale were included. AWS diagnosis relies on inspection and palpation; grading has not been validated. AWS frequency was reported in up to 85.4 % of patients. Biopsies identified venous and lymphatic pathoaetiology with five studies suggesting lymphatic involvement. Twenty-one studies reported AWS occurrence within eight post-operative weeks, but late occurrence of greater than 3 months is possible. Pain was commonly reported with shoulder abduction more restricted than flexion. AWS symptoms usually resolve within 3 months but may persist. Risk factors may include extensiveness of surgery, younger age, lower body mass index, ethnicity and healing complications. Low-quality studies suggest that conservative approaches including analgesics, non-steroidal anti-inflammatory drugs and/or physiotherapy may be safe and effective for early symptom reduction. Conclusions AWS appears common. Current evidence for the treatment of AWS is insufficient to provide clear guidance for clinical practice. Implications for Cancer Survivors Cancer survivors should be informed about AWS. Further investigation is needed into pathoaetiology, long-term outcomes and to determine effective treatment using standardised outcomes.
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Background Previously studies showed that inverse dynamics based on motion analysis and force-plate is inaccurate compared to direct measurements for individuals with transfemoral amputation (TFA). Indeed, direct measurements can appropriately take into account the absorption at the prosthetic foot and the resistance at the prosthetic knee. [1-3] However, these studies involved only a passive prosthetic knee. Aim The objective of the present study was to investigate if different types of prosthetic feet and knees can exhibit different levels of error in the knee joint forces and moments. Method Three trials of walking at self-selected speed were analysed for 9 TFAs (7 males and 2 females, 47±9 years old, 1.76±0.1 m 79±17 kg) with a motion analysis system (Qualisys, Goteborg, Sweden), force plates (Kitsler, Winterthur, Switzerland) and a multi-axial transducer (JR3, Woodland, USA) mounted above the prosthetic knee [1-17]. TFAs were all fitted with an osseointegrated implant system. The prostheses included different type of foot (N=5) and knee (N=3) components. The root mean square errors (RMSE) between direct measurements and the knee joint forces and moments estimated by inverse dynamics were computed for stance and swing phases of gait and expressed as a percentage of the measured amplitudes. A one-way Kruskal-Wallis ANOVA was performed (Statgraphics, Levallois-Perret, France) to analyse the effects of the prosthetic components on the RMSEs. Cross-effects and post-hoc tests were not analysed in this study. Results A significant effect (*) was found for the type of prosthetic foot on anterior-posterior force during swing (p=0.016), lateral-medial force during stance (p=0.009), adduction-abduction moment during stance (p=0.038), internal-external rotation moment during stance (p=0.014) and during swing (p=0.006), and flexion-extension moment during stance (p = 0.035). A significant effect (#) was found for the type of prosthetic knee on anterior-posterior force during swing (p=0.018) and adduction-abduction moment during stance (p=0.035). Discussion & Conclusion The RMSEs were larger during swing than during stance. It is because the errors on accelerations (as derived from motion analysis) become substantial with respect to the external loads. Thus, inverse dynamics during swing should be analysed with caution because the mean RMSEs are close to 50%. Conversely, there were fewer effects of the prosthetic components on RMSE during swing than during stance and, accordingly, fewer effects due to knees than feet. Thus, inverse dynamics during stance should be used with caution for comparison of different prosthetic components.
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We investigated the surface electromyogram response of six forearm muscles to falls onto the outstretched hand. The extensor carpi radialis longus, extensor carpi radialis brevis, extensor carpi ulnaris, abductor pollicis longus, flexor carpi radialis and flexor carpi ulnaris muscles were sampled from eight volunteers who underwent ten self-initiated falls. All muscles initiated prior to impact. Co-contraction is the most obvious surface electromyogram feature. The predominant response is in the radial deviators. The surface electromyogram timing we recorded would appear to be a complex anticipatory response to falling modified by the ef- fect on the forearm muscles following impact. The mitigation of the force of impact is probably more importantly through shoulder abduction and extension and elbow flexion rather than action of the forearm muscles.
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Introduction Markerless motion capture systems are relatively new devices that can significantly speed up capturing full body motion. A precision of the assessment of the finger’s position with this type of equipment was evaluated at 17.30 ± 9.56 mm when compare to an active marker system [1]. The Microsoft Kinect was proposed to standardized and enhanced clinical evaluation of patients with hemiplegic cerebral palsy [2]. Markerless motion capture systems have the potential to be used in a clinical setting for movement analysis, as well as for large cohort research. However, the precision of such system needs to be characterized. Global objectives • To assess the precision within the recording field of the markerless motion capture system Openstage 2 (Organic Motion, NY). • To compare the markerless motion capture system with an optoelectric motion capture system with active markers. Specific objectives • To assess the noise of a static body at 13 different location within the recording field of the markerless motion capture system. • To assess the smallest oscillation detected by the markerless motion capture system. • To assess the difference between both systems regarding the body joint angle measurement. Methods Equipment • OpenStage® 2 (Organic Motion, NY) o Markerless motion capture system o 16 video cameras (acquisition rate : 60Hz) o Recording zone : 4m * 5m * 2.4m (depth * width * height) o Provide position and angle of 23 different body segments • VisualeyezTM VZ4000 (PhoeniX Technologies Incorporated, BC) o Optoelectric motion capture system with active markers o 4 trackers system (total of 12 cameras) o Accuracy : 0.5~0.7mm Protocol & Analysis • Static noise: o Motion recording of an humanoid mannequin was done in 13 different locations o RMSE was calculated for each segment in each location • Smallest oscillation detected: o Small oscillations were induced to the humanoid mannequin and motion was recorded until it stopped. o Correlation between the displacement of the head recorded by both systems was measured. A corresponding magnitude was also measured. • Body joints angle: o Body motion was recorded simultaneously with both systems (left side only). o 6 participants (3 females; 32.7 ± 9.4 years old) • Tasks: Walk, Squat, Shoulder flexion & abduction, Elbow flexion, Wrist extension, Pronation / supination (not in results), Head flexion & rotation (not in results), Leg rotation (not in results), Trunk rotation (not in results) o Several body joint angles were measured with both systems. o RMSE was calculated between signals of both systems. Results Conclusion Results show that the Organic Motion markerless system has the potential to be used for assessment of clinical motor symptoms or motor performances However, the following points should be considered: • Precision of the Openstage system varied within the recording field. • Precision is not constant between limb segments. • The error seems to be higher close to the range of motion extremities.