Researchers and clinicians are increasingly using plantar pressure and force measurement system to evaluate foot functions. This research evaluates the quality and reliability of a Tekscan HR mat to study the plantar pressures and forces acting during walking, running, jumping, and standing of healthy subjects. The following regions of the foot were investigated: heel, mid foot, metatarsophalangeal joint, hallux, and the toes. The arches of both feet of the three healthy subjects in the gait analysis were presented which addresses the balancing issues of the body during locomotion. The results indicated that the peaks at the big toe (79.4 ± 8.5 N/cm2, p = 0.0001) were the maximum compared to forefoot (40.3 ± 3.3 N/cm2, p = 0.001), to midfoot (7.5 ± 1.3 N/cm2, p = 0.001), and to heel (27.8 ± 3.9 N/cm2, p = 0.0002) for jump activity. The running activity demonstrated similar results as jump where the maximum peak pressures were absorbed at the big toe region. The heel region during running (86.3 ± 12.6 N/cm2, p = 0.001) showed three times the pressure peak compared to the jump land (27.8 ± 3.9 N/cm2, p = 0.0002) activity. The measurement system proved to be highly capable of detecting heel strike and toe-off moments.
The paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVIEW cluster is developed for real-time autonomous path planning and sensor data processing. Four small form factor computers are connected over a Gigabit Ethernet local area network to form the computer cluster. Autonomous programs are distributed across the cluster for increased task parallelism to improve processing time performance. The distributed programs operating frequency for path planning and motion control is 50Hz and 12.3Hz for 0.3 megapixel robot vision system. To monitor the operation and control of the distributed LabVIEW code, network automation is integrated into the cluster software along with a performance monitor. A link between the computer motion control program and the wheelchair joystick control of the drive train is developed for the computer control interface. A perception sensor array and control circuitry is integrated with the computer system to detect and respond to the wheelchair environment. Multiple cameras are used for image processing and scanning laser rangefinder sensors for obstacle avoidance in the cluster program. A centralized power system is integrated to power the smart wheelchair along with the cluster and sensor feedback system. The on board computer system is evaluated for cluster processing performance for the smart wheelchair, incorporating camera machine vision and LiDAR perception for terrain obstacle detection, operating in urban scenarios.
The effect of different fiber blend ratios and bulk densities at similar thicknesses on air permeability and sound absorption coefficient was investigated. The raw materials used were cotton, polyester, and bi-component fibers to make acoustic nonwovens through the air-laid and thermal bonding processes. A uniform thermal-conductivity box was designed in order to make thermally bonded nonwovens with fixed thicknesses. The experimental results depict that the air flow resistance of three-layer nonwoven was 0.565 kPa&mitdott;s/m, which was about four times greater than one-layer of 0.12 kPa·s/m. Sound absorption coefficient of 20% polyester-60% cotton-20% bicomponent nonwoven with lower bulk density was greater than the 60% polyester-20% cotton-20% bicomponent nonwoven. The sound absorption coefficient varied based on which fabric side faced the testing apparatus.
The research work evaluates the quality of the sensor to perform measurements and documents its effects on the performance of the system. It also evaluates if this performance changes due to the environments and other system parameters. These environments and parameters include vibration, system friction, structural resonance, and dynamic system input. The analysis is done by modeling a gimbal camera system that requires angular measurements from inertial sensors and gyros for stabilization. Overall, modeling includes models for four different types of gyros, the gimbal camera system, the drive motor, the motor rate control system, and the angle position control system. Models for friction, structural resonance, and vibration are analyzed, respectively. The system is simulated, for an ideal system, and then includes the more realistic environmental and system parameters. These simulations are run with each of the four types of gyros. The performance analysis depicts that for the ideal system; increasing gyro quality provides better system performance. However, when environmental and system parameters are introduced, this is no longer the case. There are even cases when lower quality sensors provide better performance than higher quality sensors.
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