Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Development of an autonomous helicopter for aerial powerline inspections

Autonomous mini-helicopters have been seen as a viable option for aerial-based powerline inspections, however there are numerous research and engineering challenges in developing a system capable of achieving this task in a dependable manner. We have developed an autonomous helicopter as a research platform which will allow us to demonstrate proof-of-concept capabilities for powerline inspections. Through numerous development cycles and from flight test experience we have gained insights into the key challenges in this area. We discuss these insights, describe the helicopter platform and present our research progress in the area of obstacle avoidance for mini-helicopters.

A biomechanical study of spherical grip

Use of the hand is vital in working life due to the grabbing and pinching it performs. Spherical grip is the most commonly used, due to similarity to the gripping of a computer mouse. Knowledge of its execution and the involved elements is essential. Analysis of this exertion with surface electromyography devices (to register muscular activity) and accelerometer devices (to register movement values ) can provide multiple variables. Six subjects performed ball gripping and registered real-time electromyography (thenar region, hypothenar region, first dorsal interosseous, flexors of the wrist, flexor carpi ulnaris and extensors of the wrist muscles) and accelerometer (thumb, index, middle, ring, pinky and palm) values. The obtained data was resampled “R software” and processed “Matlab Script” based on an automatic numerical sequence recognition program. Electromyography values were normalized on the basis of maximum voluntary contraction, whilst modular values were calculated for the acceleration vector. After processing and analysing the obtained data and signal, it was possible to identify five stages of movement in accordance with the module vector from the palm. The statistical analysis of the variables was descriptive: average and standard deviations. The outcome variables focus on the variations of the modules of the vector (between the maximum and minimum values of each module and phase) and the maximum values of the standardized electromyography of each muscle. Analysis of movement through accelerometer and electromyography variables can give us an insight into the operation of spherical grip. The protocol and treatment data can be used as a system to complement existing assessments in the hand.

A kinematic and electromyographic study of grip force

Background The hand is an element of great importance to humans, as it enables us to have different grips. Its analysis, based on an accelerometer and electromyography, is critical in order to determine its operation. The processing and analysis of variables obtained by these devices offer a different approach in functional assessment. Therefore, knowledge of the muscles and elements of the hand in the grip force will offer a better approach for different interventions. Method The functionality of the hand of seven healthy subjects was parameterized and synchronized in real time based on grip force. The AcceleGlove was used to register accelerometric (fingers and palm) values and the Mega ME6000 was used for the surface electromyography and maximum voluntary contraction for the hand and forearm muscles. A computer script based on “R” and MATLAB software was developed to enable the correct interpretation of the main variables (variation of acceleration and maximum peak value of electromyography). Results The muscles of greater activity in grip was found in the hypothenar region (0.313 ± 0.148%) and the flexor ulnaris carpi (0.360 ± 0.118%), based on maximum voluntary contraction. Reference values in the module vector of the palm have proved an essential element for the identification of the movement phases. The ring and index fingers were the elements with the greatest variation of acceleration in the movement phases. Conclusion: Parameterization of the force grip and fragmentation of the registered data has been made possible due to the development of a technical procedure.

Anticipatory and reactive response to falls: Muscle synergy activation of forearm muscles

We investigated the surface electromyogram response of six forearm muscles to falls onto the outstretched hand. The extensor carpi radialis longus, extensor carpi radialis brevis, extensor carpi ulnaris, abductor pollicis longus, flexor carpi radialis and flexor carpi ulnaris muscles were sampled from eight volunteers who underwent ten self-initiated falls. All muscles initiated prior to impact. Co-contraction is the most obvious surface electromyogram feature. The predominant response is in the radial deviators. The surface electromyogram timing we recorded would appear to be a complex anticipatory response to falling modified by the ef- fect on the forearm muscles following impact. The mitigation of the force of impact is probably more importantly through shoulder abduction and extension and elbow flexion rather than action of the forearm muscles.