There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Biomechanics And Motor Control Of Human Movement

This article presents a review of the methods used in recognition and analysis of the human gait from three different approaches: image processing, floor sensors and sensors placed on the body. Progress in new technologies has led the development of a series of devices and techniques which allow for objective evaluation, making measurements more efficient and effective and providing specialists with reliable information. Firstly, an introduction of the key gait parameters and semi-subjective methods is presented. Secondly, technologies and studies on the different objective methods are reviewed. Finally, based on the latest research, the characteristics of each method are discussed. 40% of the reviewed articles published in late 2012 and 2013 were related to non-wearable systems, 37.5% presented inertial sensor-based systems, and the remaining 22.5% corresponded to other wearable systems. An increasing number of research works demonstrate that various parameters such as precision, conformability, usability or transportability have indicated that the portable systems based on body sensors are promising methods for gait analysis.

/pdf/gait-analysis-methods-an-overview-of-wearable-and-non-1kdpvp6uti.pdf

Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications.

Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges

Musculoskeletal imbalances or pathologies often develop into secondary physical conditions or complications that may affect the mobility and quality of life of people with lower-limb amputation. Using one or more prostheses causes people with amputation to alter the biomechanics of their movement. For example, people with lower-limb amputation often favor and stress their intact lower limb more during everyday activities. This can lead to degenerative changes such as osteoarthritis of the knee and/or hip joints of the intact limb. Since people with amputation spend less time on their residual limb, osteopenia and subsequent osteoporosis often occur secondary to insufficient loading through the long bones of the lower limb. A proper prosthetic fit increases the probability of equal force distribution across the intact and prosthetic limbs during ambulation, thus decreasing the risk of osteoarthritis. People with limb loss commonly complain of back pain, which is linked to poor prosthetic fit and alignment, postural changes, leg-length discrepancy, amputation level, and general deconditioning. We review the literature on secondary complications among people with lower-limb loss who are long-term prosthesis wearers.

/pdf/review-of-secondary-physical-conditions-associated-with-1bnqho5s80.pdf

Review of secondary physical conditions associated with lower-limb amputation and long-term prosthesis use

Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls.

/pdf/review-of-fall-risk-assessment-in-geriatric-populations-6gm1jshasp.pdf

Review of fall risk assessment in geriatric populations using inertial sensors

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naive Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.

/pdf/feature-selection-for-wearable-smartphone-based-human-1mck2xi8aw.pdf

Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

This study compared the kinematic and electromyographic (EMG) gait patterns of able-bodied adults at natural speed in contrast to extremely slow overground and treadmill walking speeds. Kinematic and EMG data were collected at three speeds (self-selected, 0.30 m/s, and 0.20 m/s). Eighteen subjects were evaluated for trunk and lower-limb motion and EMG of five lower-limb muscles. Significant reductions were found in segmental motion between natural speed and both slower gait speeds, accompanied by an expected reduction in cadence and stride. EMG patterns at slower speeds showed changes in timing and reduced magnitudes. Phasic timing of the proximal muscles showed the most changes with predominant coactivation, whereas the distal muscles remained consistent with the pattern at natural self-selected speed. Overground versus treadmill gait patterns revealed minimal differences. Consideration of the effects of slower walking speed may help clinicians create interventions to target primary gait deficits on overground or treadmill walking.

/pdf/electromyographic-and-kinematic-nondisabled-gait-differences-blp97cz7pp.pdf

Electromyographic and kinematic nondisabled gait differences at extremely slow overground and treadmill walking speeds.

Ambulatory assistive device use can improve functional independence following spinal cord injury and, potentially, quality of life. However, the interaction between aids and user in this population is poorly understood. Objectives: To determine the influence of walkers, crutches and canes on assisted-gait following incomplete spinal cord injury. Study design/methods: Outcome parameters evaluated in ten individuals included orthogonal forces exerted on instrumented assistive devices, walking speed, cadence, step length, trunk and thigh angles, as well as knee and ankle joint angles. Kinetic data included axial compressive force, and medio/lateral and antero/posterior bending forces. Setting: Canada. Results: Results indicated that walkers (n=5) provided the greatest vertical support (up to 100% body weight), but resulted in slow gait with a forward flexed posture. Elbow crutch users (n=3) walked faster (greater step length and cadence) and had a more upright posture than the walker users. Crutches supported up to 50% of the subject's body weight, granted lateral stability, and provided restraint in the antero/posterior direction. Canes (n=2) offered restraining and propulsive assistance, some lateral stability, and the least amount of vertical support. Conclusion: Ambulatory devices affected posture and walking speed while fulfilling various assistive functions during locomotion. The conclusion drawn is that rehabilitation specialists are advised to match device characteristics to user needs when prescribing walking aids. Sponsorship: Natural Sciences and Engineering Research Council of Canada (NSERC).

/pdf/analysis-of-assisted-gait-characteristics-in-persons-with-4uf1wxf0h3.pdf

Analysis of assisted-gait characteristics in persons with incomplete spinal cord injury

Persons with quadriceps muscle weakness are often prescribed a knee-ankle-foot orthosis that locks the knee in full extension during both stance and swing phases of gait. Locking the knee results in abnormal gait patterns characterized by hip hiking and leg circumduction during swing. The stance-control knee-ankle-foot orthosis (SCKAFO), a new type of orthosis, has emerged that permits free knee motion during swing while resisting knee flexion during stance, thereby supporting the limb during weight-bearing. This article examines various SCKAFO designs, discuss the existing design limitations, and identify remaining design challenges. Several commercial SCKAFOs have been released that incorporate different locking mechanisms. Preliminary gait studies have shown some devices to be promising; however, an important functional limitation in some SCKAFOs is dependence on specific joint angles to switch between stance and swing modes. Important design factors such as size, weight, and noise must be considered in new orthosis designs to ensure wide consumer acceptance.

https://www.rehab.research.va.gov/jour/09/46/2/pdf/yakimovich.pdf

Edward D. Lemaire

Papers

Review of fall risk assessment in geriatric populations using inertial sensors

Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

Electromyographic and kinematic nondisabled gait differences at extremely slow overground and treadmill walking speeds.

Analysis of assisted-gait characteristics in persons with incomplete spinal cord injury

Engineering Design Review of Stance-Control Knee-Ankle-Foot Orthoses