Wearable Sensor System for Lumbosacral Load Estimation by Considering the Effect of External Load

Tsuchiya, Yoshio; Kusaka, Takashi; Tanaka, Takayuki; Matsuo, Yoshikazu

doi:10.1007/978-3-319-60639-2_16

Cited by 5 publications

(2 citation statements)

References 5 publications

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“…We have been developing wearable posture and fatigue measurement devices [43,44] and assistive suits [45][46][47] using small, low-power MCUs. For this purpose, it is necessary to measure human posture in real time from sensor data using only simple arithmetic and logical operations that are possible with MCUs.…”

Section: Concept Of Approximation By Residual Correction Methodsmentioning

confidence: 99%

Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers

Kusaka¹,

Tanaka

2022

Electronics

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In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a small number of computation cycles, which may be useful when embedded in a field-programmable gate array (FPGA) or micro controller unit (MCU), or when performing many large-scale operations on a graphics processing unit (GPU). It is necessary to devise algorithms to obtain the desired calculated values without an accelerator or compiler assistance. The residual correction method (RCM) developed here can produce simple and accurate approximations of certain nonlinear functions with minimal multiply–add operations. In this study, we designed an algorithm for the approximate computation of trigonometric and inverse trigonometric functions, which are nonlinear elementary functions, to achieve their fast and accurate computation. A fast first approximation and a more accurate second approximation of each function were created using RCM with a less than 0.001 error using multiply–add operations only. This achievement is particularly useful for MCUs, which have a low power consumption but limited computational power, and the proposed approximations are candidate algorithms that can be used to stabilize the attitude control of robots and drones, which require real-time processing.

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Section: Concept Of Approximation By Residual Correction Methodsmentioning

confidence: 99%

Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers

Kusaka¹,

Tanaka

2022

Electronics

Self Cite

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“…In our past research, we used the Lagrange method for the analysis of human body motion modeled in four DoF and the design of control systems [14][15][16]. We also used the Newton-Euler method to analyze the dynamics of a 7-link (21-DoF) spinal column model for a wearable system [17,18].…”

Section: Introductionmentioning

confidence: 99%

Partial Lagrangian for Efficient Extension and Reconstruction of Multi-DoF Systems and Efficient Analysis Using Automatic Differentiation

Kusaka¹,

Tanaka

2022

Robotics

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In the fields of control engineering and robotics, either the Lagrange or Newton–Euler method is generally used to analyze and design systems using equations of motion. Although the Lagrange method can obtain analytical solutions, it is difficult to handle in multi-degree-of-freedom systems because the computational complexity increases explosively as the number of degrees of freedom increases. Conversely, the Newton–Euler method requires less computation even for multi-degree-of-freedom systems, but it cannot obtain an analytical solution. Therefore, we propose a partial Lagrange method that can handle the Lagrange equation efficiently even for multi-degree-of-freedom systems by using a divide-and-conquer approach. The proposed method can easily handle system extensions and system reconstructions, such as changes to intermediate links, for multi-degree-of-freedom serial link manipulators. In addition, the proposed method facilitates the derivation of the equations of motion-by-hand calculations, and when combined with an analysis algorithm using automatic differentiation, it can easily realize motion analysis and control the simulation of multi-degree-of-freedom models. Using multiple pendulums as examples, we confirm the effectiveness of system expansion and system reconstruction with the partial Lagrangians. The derivation of their equations of motion and the results of motion analysis by simulation and motion control experiments are presented. The system extensions and reconstructions proposed herein can be used simultaneously with conventional analytical methods, allowing manual derivations of equations of motion and numerical computer simulations to be performed more efficiently.

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Estimating Lumbar Load During Motion with an Unknown External Load Based on Back Muscle Activity Measured with a Muscle Stiffness Sensor

Tsuchiya¹,

Imamura²,

Tanaka³

et al. 2018

JRM

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A forward bending motion is essential in everyday tasks, such as carrying objects, shoveling snow, and performing farm work. However, many people suffer from lumbar pain resulting from forward bending motion, which causes a lumbar disc load owing to the changing of the lumbar shape. We have developed a wearable lumbar load estimation system, which measures the skin shape on the back using a curvature sensor. Because the lumbar load varies with the external load, the lumbar load should be estimated based on the external load. Therefore, we have developed a method for estimating an unknown external force using a muscle stiffness sensor. Muscle strength can be estimated by measuring the muscle hardness from the surface, and the relationship between the external force and the muscle force can be modeled. Using this method, we estimate the dependence of the lumbar load on external forces in real time. In addition, we simplify the calculation by converting the external load into a load resulting from a person’s own weight. We incorporate the proposed method into our wearable sensor system, estimate the lumbar load, and compare this with the results of a musculoskeletal dynamics simulation.

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Wearable Sensor System for Lumbosacral Load Estimation by Considering the Effect of External Load

Cited by 5 publications

References 5 publications

Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers

Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers

Partial Lagrangian for Efficient Extension and Reconstruction of Multi-DoF Systems and Efficient Analysis Using Automatic Differentiation

Estimating Lumbar Load During Motion with an Unknown External Load Based on Back Muscle Activity Measured with a Muscle Stiffness Sensor

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