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

Kamishima

2020

ABE

Self Cite

Lumbar loading causes increased intervertebral pressure and is an important factor in low back pain. However, it is dif cult to quantitatively judge the actions that affect lumbar load and the magnitude of lumbar load increase. Low back pain occurs not only in the workplace but also during activities of daily living. Therefore, it is necessary to investigate the factors inducing low back pain by measuring movements in various planes and determining the magnitude of the lumbar load. Accordingly, the lumbar spine should be examined during various movements. Several studies have examined vertebral bodies in the ante exion posture. However, the relationship between body exion angle and vertebral body angle during lateral exion and rotation remains unknown. In this study, we proposed an estimation method for changes in vertebral body angle during lateral exion and rotation in the lumbosacral region using a wearable sensor system we previously developed. The accuracy of the proposed estimation method was evaluated and demonstrated using X-ray images.

Section: Resultsmentioning

confidence: 99%

Relationship between Upper Body Posture Angle and Vertebral Body Posture Angle in Lateral Flexion and Rotation Posture

Tsuchiya

Kamishima

2020

ABE

Self Cite

“…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,

2022

Electronics

Self Cite

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.

“…This has enabled posture measurement on MCUs with small internal memory, where conventional mathematical libraries cannot be incorporated. Using these posture measurement algorithms for embedded systems, we previously developed wearable devices that measure and assist human body motion, mainly in the sagittal plane [ 9 , 10 , 11 ]. However, although the method of approximating nonlinear functions enabled the fast computation of plane rotations, it was difficult to extend the method to three-dimensional (3D) rotations while keeping computational costs low.…”

Section: Introductionmentioning

confidence: 99%

Stateful Rotor for Continuity of Quaternion and Fast Sensor Fusion Algorithm Using 9-Axis Sensors

Kusaka¹,

2022

Sensors

Advances in micro-electro-mechanical systems technology have led to the emergence of compact attitude measurement sensor products that integrate acceleration, magnetometer, and gyroscope sensors on a single chip, making them important devices in the field of three-dimensional (3D) attitude measurement for unmanned aerial vehicles, smartphones, and other devices. Sensor fusion algorithms for posture measurement have become an indispensable technology in cutting-edge research, such as human posture measurement using wearable sensors, and stabilization problems in robot position and posture measurement. We have also developed wearable sensors and powered suits in our previous research. We needed a technology for the real-time measurement of a 3D human body motion. It is known that quaternions can be used to algebraically handle 3D rotations; however, sensor fusion algorithms for three sensors are presently complex. This is because these algorithms deal with the post-rotation attitude (pure quaternions) rather than rotation information (the rotor) to avoid a double covering problem involving the rotor. If we are dealing with rotation, it may be possible to make the algorithm simpler and faster by dealing directly with the rotor. In this study, to solve the double covering problem involving the rotor, we propose a stateful rotor and develop a technique for uniquely determining the time-varying states of the rotor. The proposed stateful rotor guarantees the continuity of the rotor parameters with respect to angular changes, and this paper confirms its effectiveness by simulating two rotations around an arbitrary axis. In addition, we verify experimentally that a fast sensor fusion method using stateful rotor can be used for attitude calculation. Experiments also confirm that the calculated results converge to the desired rotation angle for two spatial rotations around an arbitrary axis. Since the proposed stateful rotor extends and stabilizes the definition of the rotor, it is applicable to any algorithm that deals with time-varying quaternionic rotors. In this research, an algorithm based on a multiply–add operation is designed to reduce computational complexity as a high-speed calculation for embedded systems. This method is theoretically equivalent to other methods, while contributing to power saving and the cost reduction of products.