Raziel Riemer

Biomechanical energy harvesting from human motion: theory, state of the art, design guidelines, and future directions

BackgroundBiomechanical energy harvesting from human motion presents a promising clean alternative to electrical power supplied by batteries for portable electronic devices and for computerized and motorized prosthetics. We present the theory of energy harvesting from the human body and describe the amount of energy that can be harvested from body heat and from motions of various parts of the body during walking, such as heel strike; ankle, knee, hip, shoulder, and elbow joint motion; and center of mass vertical motion.MethodsWe evaluated major motions performed during walking and identified the amount of work the body expends and the portion of recoverable energy. During walking, there are phases of the motion at the joints where muscles act as brakes and energy is lost to the surroundings. During those phases of motion, the required braking force or torque can be replaced by an electrical generator, allowing energy to be harvested at the cost of only minimal additional effort. The amount of energy that can be harvested was estimated experimentally and from literature data. Recommendations for future directions are made on the basis of our results in combination with a review of state-of-the-art biomechanical energy harvesting devices and energy conversion methods.ResultsFor a device that uses center of mass motion, the maximum amount of energy that can be harvested is approximately 1 W per kilogram of device weight. For a person weighing 80 kg and walking at approximately 4 km/h, the power generation from the heel strike is approximately 2 W. For a joint-mounted device based on generative braking, the joints generating the most power are the knees (34 W) and the ankles (20 W).ConclusionsOur theoretical calculations align well with current device performance data. Our results suggest that the most energy can be harvested from the lower limb joints, but to do so efficiently, an innovative and light-weight mechanical design is needed. We also compared the option of carrying batteries to the metabolic cost of harvesting the energy, and examined the advantages of methods for conversion of mechanical energy into electrical energy.

Evaluation of motions and actuation methods for biomechanical energy harvesting

This paper addresses energy harvesting from biomechanical motions. Such a technique is useful for powering small portable devices, such as wireless phones, music players, and digital assistants. For very low power devices, biomechanical energy may be enough to provide baseload power. In others, such as cell phones (which typically requires up to 3 W), biomechanical energy would recharge batteries for extended use between line charges, or allow for peak just-in-time power. In this paper, we consider several biomechanical motions for power generation. We evaluate actuation methods, including magnetic, piezoelectric, electrostatic, and electrical polymers for various motions in terms of energy, power, mass, and cost. We also discuss the practical issues associated with each, especially in terms of the power electronics required to connect the biomechanical sources to useful loads.

The effect of plantar flexor muscle fatigue on postural control

OBJECTIVE Previous studies have demonstrated that ankle muscle fatigue alters postural sway. Our aim was to better understand postural control mechanisms during upright stance following plantar flexor fatigue. METHOD Ten healthy young volunteers, 25.7±2.2 years old, were recruited. Foot center-of-pressure (CoP) displacement data were collected during narrow base upright stance and eyes closed (i.e. blindfolded) conditions. Subjects were instructed to stand upright and as still as possible on a force platform under five test conditions: (1) non-fatigue standing on firm surface; (2) non-fatigue standing on foam; (3) ankle plantar flexor fatigue, standing on firm surface; (4) ankle plantar flexor fatigue, standing on foam; and (5) upper limb fatigue, standing on firm surface. An average of the ten 30-s trials in each of five test conditions was calculated to assess the mean differences between the trials. Traditional measures of postural stability and stabilogram-diffusion analysis (SDA) parameters were analyzed. RESULTS Traditional center of pressure parameters were affected by plantar flexor fatigue, especially in the AP direction. For the SDA parameters, plantar flexor fatigue caused significantly higher short-term diffusion coefficients, and critical displacement in both mediolateral (ML) and anteroposterior (AP) directions. Long-term postural sway was different only in the AP direction. CONCLUSIONS Localized plantar flexor fatigue caused impairment to postural control mainly in the Sagittal plane. The findings indicate that postural corrections, on average, occurred at a higher threshold of sway during plantar flexor fatigue compared to non-fatigue conditions.

Evaluation of influence of target location on robot repeatability

This paper evaluates the influence of target location on robot repeatability. An experiment was set up to analyze the effect of the three-dimensional target location on robot repeatability. An error-analysis model to determine repeatability based on the robots kinematic model and known robot parameters was developed. Experimental results indicated that there was a significant statistical difference between repeatability at different locations in the workspace and that the height of the target point influenced repeatability. Experimental results tended to those derived from the error-analysis kinematic model. Hence, to determine the optimal target location, there is no need for extensive experimentation; instead, only a few target points can be sampled and compared to an error-analysis model.

Improving Net Joint Torque Calculations Through a Two-Step Optimization Method for Estimating Body Segment Parameters

Two main sources of error in inverse dynamics based calculations of net joint torques are inaccuracies in segmental motions and estimates of anthropometric body segment parameters (BSPs). Methods for estimating BSP (i.e., segmental moment of inertia, mass, and center of mass location) have been previously proposed; however, these methods are limited due to low accuracies, cumbersome use, need for expensive medical equipment, and/or sensitivity of performance. This paper proposes a method for improving the accuracy of calculated net joint torques by optimizing for subject-specific BSP in the presence of characteristic and random errors in motion data measurements. A two-step optimization approach based on solving constrained nonlinear optimization problems was used. This approach minimized the differences between known ground reaction forces (GRFs), such as those measured by a force plate, and the GRF calculated via a top-down inverse dynamics approach. In step 1, a series of short calibration motions was used to compute first approximations of optimized segment motions and BSP for each motion. In step 2, refined optimal BSPs were derived from a combination of these motion profiles. We assessed the efficacy of this approach using a set of reference motions in which the true values for the BSP, segment motion, GRF, and net joint torques were known. To imitate real-world data, we introduced various noise conditions on the true motion and BSP data. We compared the root mean squared errors in calculated net joint torques relative to the true values due to the optimal BSP versus traditionally-derived BSP (from anthropometric tables derived from regression equations) and found that the optimized BSP reduced the error by 77%. These results suggest that errors in calculated net joint torques due to traditionally-derived BSP estimates could be reduced substantially using this optimization approach.

Age-related differences in pelvic and trunk motion and gait adaptability at different walking speeds

This study aimed at investigating age-related changes in gait kinematics and in kinematic adaptations over a wide range of walking velocities. Thirty-four older adults and 14 younger adults walked on a treadmill; the treadmill velocity was gradually increased in increments of 0.2miles/hour (mph) (1.1-1.9mph) and then decreased in the same increments. Pelvic, trunk, upper limbs and lower limbs angular total ranges of motion (tROM), stride time, stride length, and step width were measured. The older adults had lower pelvic, trunk tROM and shorter strides and stride time compared with the younger adults. As the treadmill speed was gradually increased, the older adults showed an inability to change the pelvic list angular motions (3.1±1.3° to 3.2±1.4°) between different walking velocities, while the younger adults showed changes (5.1±1.8° to 6.3±1.7°) as a function of the walking velocity. As the walking velocity increased, the older adults increased their stride length (from 57.0±10cm to 90.2±0.1cm) yet stride times remained constant (from 1.17±0.3sec to 1.08±0.1sec), while the younger adults increased stride length and reduced stride times (from 71.4±10cm to 103.0±7.9m and from 1.45±0.2sec to 1.22±0.1sec, respectively). In conclusion, the older adults were unable to make adaptations in pelvic and trunk kinematics between different walking speeds (rigid behavior), while the younger adults showed more flexible behavior. Pelvic and trunk kinematics in different walking speeds can be used as variables in the assessment of gait in older adults.

Metabolic rate of carrying added mass: a function of walking speed, carried mass and mass location.

The effort of carrying additional mass at different body locations is important in ergonomics and in designing wearable robotics. We investigate the metabolic rate of carrying a load as a function of its mass, its location on the body and the subjects walking speed. Novel metabolic rate prediction equations for walking while carrying loads at the ankle, knees and back were developed based on experiments where subjects walked on a treadmill at 4, 5 or 6km/h bearing different amounts of added mass (up to 2kg per leg and 22kg for back). Compared to previously reported equations, ours are 7-69% more accurate. Results also show that relative cost for carrying a mass at a distal versus a proximal location changes with speed and mass. Contrary to mass carried on the back, mass attached to the leg cannot be modeled as an increase in body mass.

Biomechanical energy harvesting system with optimal cost-of-harvesting tracking algorithm

This paper presents an innovative biomechanical energy harvesting system based on the regenerative braking concept applied to the human natural motion. To determine optimal braking profile previous studies used an off-line procedure based on constant external load to determine the optimal braking profile. The new concept of this study continuously optimizes the maximum amount of energy that can be extracted during human motion while minimizing the subjects effort (metabolic rate). This is achieved by an energy harvesting system equipped with a programmable braking profile and a unique power extraction algorithm, which adaptively changes the braking profile to obtain the optimal ratio of energy to effort. These are facilitated by a BLDC generator that is connected to boost converter. A digital current programmed control of the boost converter enables an adaptive torque variation according to bio (measure of effort) and electrical feedbacks. This study focuses on the human knee joint as the energy source since the most of this joint work during level walking is negative (muscles are acting as brakes). Since this work is preliminary and more oriented to the novel concept of adaptive profile and optimal power extraction, the operation of the energy harvester is demonstrated on a full-scale laboratory prototype based on a walking emulator. The results exhibit ultimate power extraction capabilities as well as adaptation to the walking pattern.

Energetically Optimal Gait Transition Velocities of a Quadruped Robot

Determining gait patterns with low energy consumption per distance traveled are important for increasing robots operation range. These gait patterns, a function of the robots speed and structure, are generally determined by optimization processes. In contrast to previous studies that examined the energy consumption of several gait patterns at specific travel velocities, this study presents an optimization process that determines the optimal gait pattern for a range of velocities. In the first part of the study, three optimization methods are compared - the genetic algorithm, the radial-basis function method and the Nelder-Mead simplex. Results indicated that the preferred optimization method is genetic algorithm. In the second part of the study, we reduced the number of optimization variables, using constraints that represent known gait patterns. This led to a reduction of approximately 50% in optimization runtime, while maintaining similar energy consumption per distance as achieved in the first part of the study.

Modeling and analysis of brushless generator based biomechanical energy harvesting system

An analysis and modeling approach of an electromechanical harvesting system based on a brushless generator (BLG) is presented and evaluated. The approach is based on an electrical analog of the mechanical components and was verified by modeling a knee joint harvesting system. Good agreement was found between the model predictions and the experimental results. New harvesting strategies based on energy storage by the BLG moment of inertia are suggested and examined.