Narrow Results

Objective: To compare the effectiveness of mobile video-guided home exercise program and standard paper-based home exercise program.

Methods: Eligible participants were randomly assigned to either experimental group with mobile video-guided home exercise program or control group with home exercise program in a standard pamphlet for three months. The primary outcome was exercise adherence. The secondary outcomes were self-efficacy for exercise by Self-Efficacy for Exercise (SEE) Scale; and functional outcomes including mobility level by Modified Functional Ambulatory Category (MFAC) and basic activities of daily living (ADL) by Modified Barthel Index (MBI). All outcomes were captured by phone interviews at 1 day, 1 month and 3 months after the participants were discharged from the hospitals.

Results: A total of 56 participants were allocated to the experimental group $(n=27)$ and control group $(n=29)$. There were a significant between-group differences in 3-months exercise adherence (experimental group: 75.6%; control group: 55.2%); significant between-group differences in 1-month SEE (experimental group: 58.4; control group: 43.3) and 3-month SEE (experimental group: 62.2; control group: 45.6). For functional outcomes, there were significant between-group differences in 3-month MFAC gain (experimental group: 1.7; control group: 1.0). There were no between-group differences in MBI gain.

Conclusion: The use of mobile video-guided home exercise program was superior to standard paper-based home exercise program in exercise adherence, SEE and mobility gain but not basic ADL gain for patients recovering from stroke.

Soft robotics are robotic systems made of materials that are similar in softness to human soft tissues. Recent medical soft robot designs, including rehabilitation, surgical, and diagnostic soft robots, are categorized by application and reviewed for functionality. Each design is analyzed for engineering characteristics and clinical significance. Current technical challenges in soft robotics fabrication, sensor integration, and control are discussed. Future directions including portable and robust actuation power sources, clinical adoptability, and clinical regulatory issues are summarized.

Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user’s intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was $98.1\pm 4.9\%$ for the neurologically intact subjects and $90.0\pm 13.9\%$ for the SCI subjects. The total lag of the system was approximately 250ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.

The basic concepts for exoskeletal systems have been suggested for some time with applications ranging from construction, manufacturing and mining to rescue and emergency services. In recent years, research has been driven by possible uses in medical/rehabilitation and military applications. Yet there are still significant barriers to the effective use and exploitation of this technology. Among the most pertinent of these factors is the power and actuation system and its impact of control, strength, speed and, perhaps most critically, safety. This work describes the design, construction and testing of an ultra low-mass, full-body exoskeleton system having seven degrees of freedom (DOFs) for the upper limbs and five degrees of freedom (DOFs) for each of the lower limbs. This low mass is primarily due to the use of a new range of pneumatic muscle actuators as the power source for the system. The work presented will show how the system takes advantage of the inherent controllable compliance to produce a unit that is powerful, providing a wide range of functionality (motion and forces over an extended range) in a manner that has high safety integrity for the user. The general layout of both the upper and the lower body exoskeleton is presented together with results from preliminary experiments to demonstrate the potential of the device in limb retraining, rehabilitation and power assist (augmentation) operations.

Analysis of human ability to move the body (hand, feet, etc.) is one of the major issues in rehabilitation science. For this purpose, scientists analyze different signals govern from human body. Electromyography (EMG) signal is the main indicator of human movement that can be analyzed using different techniques in order to classify different movements. In this paper, we analyze the complex non-linear structure of EMG signal from subjects while they underwent three exercises that include basic movements of the fingers and of the wrist, grasping and functional movements, and force patterns. For this purpose, we employ fractal dimension as indicator of complexity. The result of our analysis showed that the EMG signal experiences the greatest complexity when subjects think to press combinations of fingers with an increasing force (force pattern). The method of analysis employed in this research can be widely applied to analyze and classify different types of human movements.

Efforts to preserve the biodiversity of the Philippine islands and to simultaneously sustain human food production, led to the development of a "Closed Canopy and High Diversity Forest Farming System", popularly termed "Rainforestation Fanning". The system is aiming to replace the more destructive forms of "kaingin" or slash and burn practices, form a buffer zone around the primary forests, protect its biodiversity, help maintain the water cycle of the islands, and provide farmers with a stable and higher income.

Contrary to the conventional paradigm of farm management, the concept works with the hypothesis that a farming system is increasingly more sustainable the closer its physical structure and species composition are to the original local rainforest. Consequently, the biodiversity and physico-chemical diversity of the remaining rainforests of Leyte are studied in detail. In a holistic approach, all major ecosystems connected physically, biologically or through the activity of man are included in the research.

In field trials, more than 100 selected local tree species are tested for their performance in achieving a 3-storeyed and maximal diverse rainforest association. Crop production enriches the system through shade-requiring understorey species of Colocasia and Xanthosoma, and climbers like species of Dioscorea and rattan are attached to the faster growing trees.

A major drawback is the scarcity of seeds from highly valued tree species due to the almost complete extinction of the lowland rainforest and to ongoing selective timber poaching which is specifically eliminating mother trees. Hence, environmental education plays a major part in the overall approach, which also includes efforts to protect seed sources and can extend to the conservation of marine sanctuaries to emphasize the interconnectedness of all island ecosystems and man's role in his coexistence with nature.

The objective of this study was to assess evidence for the efficacy and effectiveness of Chinese qigong exercise in rehabilitative programs among cardiac patients. Thirteen databases were searched through to November 2010, and all controlled clinical trials on Chinese qigong exercise among patients with chronic heart diseases were included. For each included study, data was extracted and validity was assessed. Study quality was evaluated and summarized using both the Jadad Scale and the criteria for levels of evidence. Seven randomized controlled trials (RCTs) and one non-randomized controlled clinical trial (CCT) published between 1988 and 2007 met the inclusion criteria. In total, these studies covered 540 patients with various chronic heart diseases including atrial fibrillation, coronary artery disease, myocardial infarct, valve replacement, and ischemic heart disease. Outcome measures emerged in these studies included subjective outcomes such as symptoms and quality of life; and objective outcomes such as blood pressure, ECG findings, and exercise capacity, physical activity, balance, co-ordination, heart rate, and oxygen uptake. Overall, these studies suggest that Chinese qigong exercise seems to be an optimal option for patients with chronic heart diseases who were unable to engage in other forms of physical activity; however, its efficacy and effectiveness in cardiac rehabilitation programs should be further tested.

Analysis of human movements is an important category of research in biomedical engineering, especially for the rehabilitation purpose. The human’s different movements are usually investigated by analyzing the movement signals. Based on the literatures, fewer efforts have been made in order to investigate how human movements are represented in the brain. In this paper, we decode the movements’ directions of wrist by complexity analysis of Magnetoencephalography (MEG) signal. For this purpose, we employ fractal theory. In fact, we investigate how the complexity of MEG signal changes in case of different wrist movements’ directions. The results of our analysis showed that MEG signal has different level of complexity in response to different movement’s directions. The employed methodology in this research is not limited to the analysis of MEG signal in response to wrist movement, however, it can be applied widely to analyze the influence of different factors (stimuli) on complex structure of other brain signals such as Electroencephalography (EEG) and fMRI signals.

Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity. Minimizing the recalibration times is important to reduce the setup preparation and maximize the effective therapy time. To date, a systematic analysis of the effect of recalibration strategies in EEG-driven interfaces for motor rehabilitation has not yet been performed. Data from patients with stroke (4 patients, 8 sessions) and spinal cord injury (SCI) (4 patients, 5 sessions) undergoing two different paradigms (self-paced and cue-guided, respectively) are used to study the performance of the EEG-based classification of motor intentions. Four calibration schemes are compared, considering different combinations of training datasets from previous and/or the validated session. The results show significant differences in classifier performances in terms of the true and false positives (TPs) and (FPs). Combining training data from previous sessions with data from the validation session provides the best compromise between the amount of data needed for calibration and the classifier performance. With this scheme, the average true (false) positive rates obtained are 85.3% (17.3%) and 72.9% (30.3%) for the self-paced and the cue-guided protocols, respectively. These results suggest that the use of optimal recalibration schemes for EEG-based classifiers of motor intentions leads to enhanced performances of these technologies, while not requiring long calibration phases prior to starting the intervention.

Analysis of human movements is an important category of research in biomedical engineering, especially for the rehabilitation purpose. The movement of limbs is investigated usually by analyzing the movement signals. Less efforts have been made to investigate how neural that correlate to the movements, are represented in the human brain. In this research, for the first time we decode the limb movements by fractal analysis of Electroencephalogram (EEG) signals. We investigated how the complexity of EEG signal changes in different limb movements in motor execution (ME), and motor imagination (MI) sessions. The result of our analysis showed that the EEG signal experiences greatest level of complexity in elbow flexion and hand-close movements in ME, and MI sessions respectively. On the other hand, the lowest level of complexity of EEG signal belongs to hand-open and rest condition in ME, and MI sessions, respectively. Employing fractal theory in analysis of bio signals is not limited to EEG signal, and can be further investigated in other types of human’s bio signals in different conditions. The result of these investigations can vastly been employed for the rehabilitation purpose.

This paper proposes a new method to improve accuracy and real-time performance of inertial joint angle estimation for upper limb rehabilitation applications by modeling body acceleration and adding low-cost markerless optical position sensors. A method based on a combination of the 3D rigid body kinematic equations and Denavit-Hartenberg (DH) convention is used to model body acceleration. Using this model, body acceleration measurements of the accelerometer are utilized to increase linearization order and compensate for body acceleration perturbations. To correct for the sensor-to-segment misalignment of the inertial sensors, position measurements of a low-cost markerless position sensor are used. Joint angles are estimated by Extended Kalman Filter (EKF) and compared with Unscented Kalman Filter (UKF) in terms of performance. Simulations are performed to quantify the existing error and potential improvements achievable by the proposed method. Experiments on a human test subject performing an upper limb rehabilitation task is used to validate the simulation results in realistic conditions.

Log landings and skid trails made by bulldozers during logging operations recover much more slowly than adjacent areas which were not traversed by heavy machinery. Even decades after completion of logging operations the vegetation on such areas is sparse with few or no tree species. Where logging is unplanned, log landings and skid trails can cover up to 40% of the total forest area resulting in a loss of productive forest. Therefore, artificial rehabilitation may be needed for such sites. A major constraint to both natural and artificial recovery is the poor physical and chemical properties of the soils on log landings and skid trails. Repeated use by heavy machinery results in severe soil compaction which leads to poor root development, low water availability and high rates of erosion. In addition, most of the topsoil is removed from log landings and skid trails by bulldozers during logging operations. A very high proportion of nutrients are found in the top few centimetres of rainforest soil, so removal of the topsoil exposes the very infertile subsoil. Despite these adverse conditions, it has been shown that some seedlings of some dipterocarp species can survive and grow on log landings if soil amelioration treatments are used. The various techniques available for planting and subsequent maintenance are discussed. The cost of rehabilitation ranges between approximately US$ 1,000 and US$ 1,500 per hectare.

Multi-degrees of freedom (DOF) parallel robot, due to its compact structure and high operation accuracy, is a promising candidate for medical rehabilitation devices. However, its controllability relating to the nonlinear characteristics challenges its interaction with human subjects during the rehabilitation process. In this paper, we investigated the control of a parallel robot system using fuzzy sliding mode control (FSMC) for constructing a simple controller in practical rehabilitation, where a fuzzy logic system was used as the additional compensator to the sliding mode controller (SMC) for performance enhancement and chattering elimination. The system stability is guaranteed by the Lyapunov stability theorem. Experiments were conducted on a lower limb rehabilitation robot, which was built based on kinematics and dynamics analysis of the 6-DOF Stewart platform. The experimental results showed that the position tracking precision of the proposed FSMC is sufficient in practical applications, while the velocity chattering had been effectively reduced in comparison with the conventional FSMC with parameters tuned by fuzzy systems.

The study of lower limb movements plays an important role in many fields, such as rehabilitation and treatment of disabled patients, detection, and monitoring of daily life, as well as the interaction between people and machine, like the application of intelligent prosthetics. In this paper, the wireless device was used to collect the mechanomyography (MMG) signals of four thigh muscles (rectus femoris, vastus lateralis, vastus medialis, and semitendinosus) and the attitude angle of rectus femoris. High precision was achieved in 11 gait movements, including 3 static activities, 4 dynamic transition activities, and 4 dynamic activities. It has been verified that the hidden Markov model (HMM) could not only be applied to the MMG-based gait recognition with high veracity but also support comparative analysis between support vector machine (SVM) and quadratic discriminant analysis (QDA). In addition, the experiment was conducted from the perspectives of feature selections, channel combinations, and muscle contribution rates. The results show that the average classification accuracy of dynamic motions based on MMG is 98.27%, while based on attitude angle, the average recognition rate of static motions and dynamic transition motions could achieve 98.33% and 100%, respectively. Generally, the average recognition rate of 11 gait motions is 98.91%.

Active Exoskeletons can become a powerful tool for therapists for the rehabilitation of patients suffering from neurophysiological conditions. The mathematical modeling for estimating joint moments required for human walking movement proves difficult due to the high number of degrees of freedom (DoF) and the complexity of movement. Another factor that poses a problem is the unavailability of ground reaction force (GRF) data, which must be present as the external applied forces in the model. This paper presents a machine learning-based approach for predicting joint moments for walking that uses only the kinematic data of the subjects. The dataset used includes data available from published sources as well as data collected by the authors. The predictions have been compared with and validated using the joint moment results from optimization-based inverse dynamics model in OpenSim. Subsequently, a concept design of a lower limb exoskeleton has been presented and actuator requirements for the same are set according to the joint moment predictions for a specific human subject. The prototype design includes eight rotational degrees of freedom (DOF) in total, i.e., four degrees of freedom per leg: two at the hip joint, one at the knee joint and one at the ankle joint. The feasibility study of the prototype has been carried out with the help of finite element analysis (FEA) in Ansys software after utilizing the weight of the human being and joint rotations as inputs to the model. Based on the results obtained from the FEM, the design has been optimized to ensure structural stability.

Background: Physiotherapists play a key role in sports injury rehabilitation within the sports healthcare team. A strong athlete–physiotherapist relationship is necessary for effective treatment and shaping of athletes’ expectations of injury rehabilitation. Hence, it is necessary to factor the injured athletes’ expectations in structuring a rehabilitation program.

Objective: The aim of this study was to determine athletes’ expectations about physiotherapy in sports injury rehabilitation.

Methods: We performed a cross-sectional survey in which data was collected using the expectation about athletic training (EAAT) questionnaire from 120 recruited athletes of different sporting disciplines. Percentages, means and standard deviations of the expectation scores were computed. Associations between socio-demographic characteristics and athletes’ expectations of physiotherapy in sports injury rehabilitation were analyzed with the chi-square test. Differences between the athletes’ expectations of physiotherapy and demographic characteristics were also analyzed with Kruskal–Wallis and Mann–Whitney tests.

Results: The study revealed that there was no significant difference ($p>0.05$) between gender, injury type, physiotherapy experience and mental skills experience and the athletes’ expectations. There was a significant difference ($p<0.05$) between competition level and athletes’ expectations.

Conclusion: It was concluded that athletes in the Greater Accra Region have high expectations of physiotherapy in injury rehabilitation; thus sports physiotherapists would need to enhance their communication with athletes which may also help them better understand the risks, benefits, timeline and rehabilitation approach.

Dipterocarps cannot be successfully used as primary species in Imperata grassland reforestation. First the grass has to be suppressed by fast-growing species, which are able to provide suitable growing conditions for dipterocarp seedlings. Nitrogen fixing Paraserianthes falcataria and Acacia mangium are possible species for this purpose, but local pioneer species may have potential as well. After the fast-growing plantation has been established, successful planting of dipterocarps becomes technically possible. Intensive plantation tending has to be continued after the establishment phase. When planting dipterocarps under fast-growing nurse trees on grasslands, the species selection should be focused on species known to be adaptable to degraded soil conditions and extreme microclimate. Possible species can be found in fast-growing, light or medium hardwood dipterocarp genera, e.g., Anisoptera sp., Dryobalanops sp., Hopea sp. and Shorea sp. More information on suitable species, and their site requirements and mycorrhizal formations is needed. Plantation mixtures are more complicated to manage than the pure stands of exotics. In spite of the problems, results indicate good prospects for diversifying the species composition of forest plantations on former Imperata cylindrica grasslands. Combinations of fast-growing species and selected dipterocarps create alternatives to the exploitation of remaining natural forests. Despite the long time period needed, the method can be used both for wood production and gradual restoration of natural rainforest ecosystems.

Walking is for humans an essential task in our daily life. However, there is a huge (and growing) number of people who have this ability diminished or are not able to walk due to motor disabilities. In this paper, a system to detect the start and the stop of the gait through electroencephalographic signals has been developed. The system has been designed in order to be applied in the future to control a lower limb exoskeleton to help stroke or spinal cord injured patients during the gait. The brain–machine interface (BMI) training has been optimized through a preliminary analysis using the brain information recorded during the experiments performed by three healthy subjects. Afterward, the system has been verified by other four healthy subjects and three patients in a real-time test. In both preliminary optimization analysis and real-time tests, the results obtained are very similar. The true positive rates are $54.8\%$ and $56.1\%$ respectively. Regarding the false positive per minute, the values are also very similar, decreasing from 2.66 in preliminary tests to 1.90 in real-time. Finally, the average latencies in the detection of the movement intentions are 794 and 798ms, preliminary and real-time tests respectively.

Squatting has received considerable attention in sports and is commonly utilized in daily activities. Knowledge of the squatting biomechanics in terms of its speed and depth may enhance exercise selection when targeting for sport-specific performance improvement and injury avoidance. Nonetheless, these perspectives have not been consistently reported. Hence, this preliminary study intends to quantify the kinematics, kinetics, and energetics in squat with different depths and speeds among healthy young adults with different physical activity levels; i.e., between active and sedentary groups. Twenty participants were administered to squat at varying depths (deep, normal, and half) and speeds (fast, normal, and slow). Motion-capture system and force plates were employed to acquire motion trajectories and ground reaction force. Joint moment was obtained via inverse dynamics, while power was derived as a product of moment and angular velocity. Higher speeds and deeper squats greatly influence higher joint moments and powers at the hip ($p<0.05$) and knee ($p<0.05$) than ankle, signifying these joints as the prime movers with knee as the predominant contributor. These preliminary findings show that the knee-strategy and hip-strategy were employed in compensating speed and depth manipulations during squatting. In certain contexts, appreciating these findings may provide clinically relevant implications, from the performance and injury avoidance viewpoint, which will ameliorate the physical activity level of practitioners.

Background: The objective was to study the hypotheses that an advanced zone II flexor tendon rehabilitation protocol would avoid rupture, achieve a high range of excursion, and minimize interphalangeal contracture during both the early phases and at the conclusion of healing. We also proposed the null hypothesis of no difference between any two of the zone II subdivisions.

Methods: Fifty-one consecutive adult patients with zone II flexor tendon repairs of a single finger were retrospectively evaluated on an active contraction rehabilitation protocol with no splint, no tenodesis protection, and immediate full composite extension. There were 38 males and 13 females with a mean age of 39 years (range 18–69) involving 15 index, 7 long, 6 ring, and 23 small fingers. Repairs were located in flexor subzone IIA for 8 fingers; subzone IIB, 14; subzone IIC, 19; and subzone IID, 10. Differences in outcome between any two subzones were compared by T-test with p < 0.05.

Results: Mean active arcs of motion in degrees at 3 weeks post repair were PIP 1-93; DIP 0-44; and total active motion (TAM) 221. At 6 weeks PIP 2–98; DIP 1–51; and TAM 236. At 10–12 weeks PIP 1–101; DIP 1–56; and TAM 246. Final TAM by flexor subzone IIA was 243; IIB, 251; IIC, 246; and IID, 246. There were no significant differences between any two subzones. Mean final DASH score was 5. There were no ruptures.

Conclusions: The results support the hypotheses. Outcomes of the therapy protocol demonstrated the lack of interphalangeal joint flexion contractures, high range of total active motion achieved early and sustained, and no ruptures. No differences were identified between and two of the flexor subzones.