DEVELOPING A FOOTSWITCH DEVICE TO ASSESS THE LIKELIHOOD OF FALLS IN AT-RISK POPULATIONS

Falls are one of the major cause of injuries, reduced functioning and even mortality in older adults. Most of the falls occur during walking, so considering the mechanics of gait during walking can provide insight to identify the risk of fall in this population. A component of walking mechanics associated with falling in the elderly is gait variability (i.e. the inherent natural fluctuations between strides). Healthy states are associated with an optimal level of movement variability reflecting the adaptability of the underlying control system, while pathological gait can be either too regular, or periodic, or too random and disordered. In this study we aim to develop a footswitch device including a programmed microprocessor electronic board and insoles with pressure sensors to measure gait variability and evaluate fall risk in at-risk populations (e.g. the elderly). For this purpose, we are going to recruit twenty healthy older adults and ten elderly who experienced a fall. Then, participants will be asked to perform three clinical functional tests including 1) timed up and go, 2) Berg Balance scale, and 3) dynamic gait index test. Moreover, they’ll be asked to walk on a treadmill for 10 minutes at 0.8 m.s-1 with foot switch prototype. Stride interval time series will be extracted from the foot switch data and gait variability will be assessed using nonlinear methods. Finding association between the gait variability results and the clinical functional tests can inform about ways to determine the risk of falling with more accurate and inexpensive gait assessments

OPTIMIZATION OF THE MUSCULOSKELETAL SIMULATION IN ESTIMATION OF METABOLIC COST

Energy from food is supplied to the human body in the form of chemical energy in the muscles. This metabolic energy expenditure is one of the main determinants of the way we walk, and indirect calorimetry measurements are an essential tool for understanding how increases in metabolic cost restrict the mobility of clinical populations. Respiratory oxygen consumption measurements allow recording of the average metabolic cost of walking. However, the time required for these measurements prevents assessing metabolic rate in patients who cannot walk long enough. Musculoskeletal modeling techniques allow to estimate average muscle energy expenditure during locomotion in conjunction with muscle metabolic rate equations. One of the most widely used equations for estimating human metabolic cost (i.e., Umberger) is based on a mix of literature sources, including ex-vivo and animal experiments. However, a wide variety of parameter derivations can affect the agreement between model predictions and experimental results. Although a reasonable agreement was found between model predictions and experimental results, enhancing the level of agreement is possible by improving the coefficients and options that come from non-human experiments. In this project, we aim to optimize the coefficients and options in the Umberger model to improve its overall accuracy and agreement with experimental results compared to previous literature. The cost function of the optimization will be to minimize the error in the estimated stride average metabolic cost from the stride average indirect calorimetry

Differences between joint-space and musculoskeletal estimations of metabolic rate time profiles

Motion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate within the stride cycle. A variety of methods and metabolic equations have been proposed, including metabolic time profile estimations based on joint parameters. It is unclear whether differences in estimations are due to differences in experimental data or due to methodological differences. This study aimed to compare two methods for estimating the time profile of metabolic rate, within a single dataset. Knowledge about the consistency of different methods could be useful for applications such as detecting which part of the gait cycle causes increased metabolic cost in patients. Here we compare estimations of metabolic rate time profiles using a musculoskeletal and a joint-space method. The musculoskeletal method was driven by kinematics and electromyography data and used muscle metabolic rate equations, whereas the joint-space method used metabolic rate equations based on joint parameters. Both estimations of changes in stride average metabolic rate correlated significantly with large changes in indirect calorimetry from walking on different grades showing that both methods accurately track changes. However, estimations of changes in stride average metabolic rate did not correlate significantly with more subtle changes in indirect calorimetry due to walking with different shoe inclinations, and both the musculoskeletal and joint-space time profile estimations did not correlate significantly with each other except in the most downward shoe inclination. Estimations of the relative cost of stance and swing matched well with previous simulations with similar methods and estimations from experimental perturbations. Rich experimental datasets could further advance time profile estimations. This knowledge could be useful to develop therapies and assistive devices that target the least metabolically economic part of the gait cycle

Modular footwear that partially offsets downhill or uphill grades minimizes the metabolic cost of human walking

Walking on different grades becomes challenging on energetic and muscular levels compared to level walking. While it is not possible to eliminate the cost of raising or lowering the centre of mass (COM), it could be possible to minimize the cost of distal joints with shoes that offset downhill or uphill grades. We investigated the effects of shoe outsole geometry in 10 participants walking at 1 m s−1 on downhill, level and uphill grades. Level shoes minimized metabolic rate during level walking (Psecond-order effect \u3c 0.001). However, shoes that entirely offset the (overall) treadmill grade did not minimize the metabolic rate of walking on grades: shoes with a +3° (upward) inclination minimized metabolic rate during downhill walking on a −6° grade, and shoes with a −3° (downward) inclination minimized metabolic rate during uphill walking on a +6° grade (P interaction effect = 0.023). Shoe inclination influenced (distal) ankle joint parameters, including soleus muscle activity, ankle moment and work rate, whereas treadmill grade influenced (whole-body) ground reaction force and COM work rate as well as (distal) ankle joint parameters including tibialis anterior and plantarflexor muscle activity, ankle moment and work rate. Similar modular footwear could be used to minimize joint loads or assist with walking on rolling terrain

Design and development of a semi-rigid hip exoskeleton to reduce metabolic cost

Robotic exoskeletons can reduce metabolic cost in healthy individuals and restore mobility in patients with peripheral artery disease (PAD). PAD is a cardiovascular disease produced by atherosclerosis of the leg arteries. The primary symptom of PAD is claudication or pain in the legs during walking, which severely shortens the distance a patient can walk. Knowing that up to 40% of the metabolic cost of walking comes from the hip muscles, different groups have been developing rigid exoskeletons and soft exosuits that assist the hip. Assisting at the hip has the advantage that the exoskeleton mass is positioned close to the center of mass, which minimizes the energy cost of the added mass. Soft exosuits have the advantage that they allow greater freedom of movement. However, soft exosuits often cannot apply the same torque magnitudes as rigid exoskeletons, and they rely on friction with the skin to remain anchored. The purpose of this work was to develop a semi-rigid hip exoskeleton that can connect to and be powered by an existing actuation unit, to address the limitations of current existing soft exosuits. We evaluated the device performance by analyzing the match between desired and actual torque applied to the hip joint. Our exoskeleton\u27s semi-rigid design introduces advantages in comfort and efficiency of control in patients with PAD because it requires less friction and compression than soft exosuits. Our initial work demonstrates a good match between the desired and actual torque that the exoskeleton was able to generate for each leg

HOW CAN ACTUATION TIMING AND MAGNITUDE OF A BILATERAL SEMI-RIGID HIP EXOSKELETON OPTIMIZE METABOLIC COST

Semi-rigid exoskeletons could combine some advantages of rigid and soft approaches. The purpose of this study was to investigate the effects of timing and magnitude of assistance from a semi-rigid hip exoskeleton. For ten participants, we tested ten conditions that were combinations of 5 different end-timings, ranging from 21% to 49%, and 2 different moment magnitudes ranging from 0.06 to 0.12 Nm.kg-1. The participants walked in two reference conditions: a condition without actuation and a condition without the exoskeleton. A semi-rigid hip exoskeleton could alter metabolic rate. However, to produce a net assistive effect, it is necessary to design a lighter, more conforming device. In both actuation magnitude levels, the optimal end-timing was close to the maximum range, similar to findings from another study with human-in-the-loop optimization of a soft hip exosuit. This could indicate that the optimal timing with a semi-rigid device is not very different from a fully-soft prototype

Metabolically efficient walking assistance using optimized timed forces at the waist

The metabolic rate of walking can be reduced by applying a constant forward force at the center of mass. It has been shown that the metabolically optimal constant force magnitude minimizes propulsion ground reaction force at the expense of increased braking. This led to the hypothesis that selectively assisting propulsion could lead to greater benefits. We used a robotic waist tether to evaluate the effects of forward forces with different timings and magnitudes. Here, we show that it is possible to reduce the metabolic rate of healthy participants by 48% with a greater efficiency ratio of metabolic cost reduction per unit of net aiding work compared with other assistive robots. This result was obtained using a sinusoidal force profile with peak timing during the middle of the double support. The same timing could also reduce the metabolic rate in patients with peripheral artery disease. A model explains that the optimal force profile accelerates the center of mass into the inverted pendulum movement during single support. Contrary to the hypothesis, the optimal force timing did not entirely coincide with propulsion. Within the field of wearable robotics, there is a trend to use devices to mimic biological torque or force profiles. Such bioinspired actuation can have relevant benefits; however, our results demonstrate that this is not necessarily optimal for reducing metabolic rate

THE EFFECT OF ARM SWING ON COUNTERMOVEMENT VERTICAL JUMP PERFORMANCE

Vertical jumping is one of the popular ways to evaluate ankle-knee efficiency in athletic population. Arm swing can play a crucial role in enhancing vertical jump performance. This study aimed to address the differences in kinetic and kinematic parameters during countermovement jump motion with arm swing (AS) and no arm swing (NAS). We used OpenSim to examine the efficacy of AS in reducing the impulse applied to the body and changes in range of lower limb joint angles at landing instant. We calculated the maximum vertical peak of the ground reaction force and impulse generated at landing in two different conditions (AS and NAS). Participants were asked to perform ten countermovement jumps, five for AS and five for AS. We measured kinematics and kinetics by using motion capture and ground reaction forces using a force treadmill. Means and standard deviations of kinetic and kinematic outcomes were calculated across conditions. Hip and ankle power were significantly higher during NAS compared to AS condition at landing instant. The results of this study showed that AS jump could reduce the generated powers at the ankle and hip joints during instant landing compared to the NAS condition. This could be due to the compensatory role of the shoulder and elbow joints to prepare the body for the landing phase. The study did not have enough statistical power to reveal differences between other kinetic and kinematic components of jumping, which could be further enhanced by increasing the sample size

Estimating variations in metabolic cost within the stride cycle during level and uphill walking

Indirect calorimetry provides the average cost of a stride cycle and prevents from identifying which part of the gait cycle causes increased metabolic cost in patients, however, recent simulation methods allow estimating the time profile of metabolic cost within the stride cycle. In this study, we compare the estimations of the time profile of the metabolic cost of two simulation methods for level and uphill walking. We used kinematic, kinetic and electromyography data from level and uphill walking (one participant) to estimate the time profiles of metabolic cost using the muscle-level metabolic model of Umberger using electromyography and kinematic data into a musculoskeletal simulation. We estimated the time profile of metabolic cost based on the joint moments and joint angular velocities (Roberts et al.). Both methods show a phase of high metabolic cost in the first 10% of the gait cycle. The Umberger method reveals another phase with a high metabolic cost during the second half of stance whereas the Roberts et al. method shows a phase with high metabolic cost in early swing phase. Both methods estimated an increase in metabolic cost with uphill walking, in line with indirect calorimetry measurements. There is no experimental measurement of the time profile of metabolic cost that allows identifying which of the two estimation methods is more accurate. The fact that both methods show moderate similarity and can detect the increase in metabolic cost during uphill walking suggest that they could be useful as an input for optimization methods of assistive devices