The “Federica” Hand

Hand prostheses partially restore hand appearance and functionalities. In particular, 3D printers have provided great opportunities by simplifying the manufacturing process and reducing costs. The “Federica” hand is 3D-printed and equipped with a single servomotor, which synergically actuates its five fingers by inextensible tendons; no springs are used for hand opening. A differential mechanical system simultaneously distributes the motor force on each finger in predefined portions. The proportional control of hand closure/opening is achieved by monitoring muscle contraction by means of a thin force sensor, as an alternative to EMG. The electrical current of the servomotor is monitored to provide sensory feedback of the grip force, through a small vibration motor. A simple Arduino board was adopted as the processing unit. A closed-chain, differential mechanism guarantees efficient transfer of mechanical energy and a secure grasp of any object, regardless of its shape and deformability. The force sensor offers some advantages over the EMG: it does not require any electrical contact or signal processing to monitor muscle contraction intensity. The activation speed (about half a second) is high enough to allow the user to grab objects on the fly. The cost of the device is less then 100 USD. The “Federica” hand has proved to be a lightweight, low-cost and extremely efficient prosthesis. It is now available as an open-source project (CAD files and software can be downloaded from a public repository), thus allowing everyone to use the “Federica” hand and customize or improve it.

Changes in the Linear Relationship between Muscle Contraction Intensity and Muscle Hardness after Rectus Femoris Muscle Strain

Objective. Joint torque differences between healthy and rehabilitated legs are often measured as a clinical index of recovery from muscle strain injury. Unfortunately, it should be noted that this is a questionable evaluation measure of the muscle after injury because it is a composite value including related cooperating muscles. Meanwhile, the use of ultrasound elastography for the measurement of individual muscle mechanical properties (i.e., muscle hardness) has recently expanded. The purpose of this study was to examine, using ultrasound elastography, the differences in the linear relationship between muscle contraction intensity and muscle hardness during knee extension in athletes who had recovered from grade II rectus femoris muscle strain injury through comparison of the healthy and rehabilitated legs. Methods. Six athletes participated. Rectus femoris muscle hardness, determined during isometric contraction at 10%, 20%, 30%, and 40% of maximum voluntary contraction, was evaluated using ultrasound strain elastography. Results and Conclusion. The results indicated that for the healthy legs, the strain ratios, as indicated by muscle hardness, decreased linearly (became harder) with contraction intensity, but the strain ratios for the rehabilitated legs decreased nonlinearly. These results show the danger of judging the recovery period using only the difference between healthy and rehabilitated muscle strengths and the importance of evaluating individual muscles.

Relationship between Isometric Muscle Force and Fractal Dimension of Surface Electromyogram

The relationship between fractal dimension of the surface electromyogram (sEMG) and the intensity of muscle contraction is still controversial in simulated and experimental conditions. To support the use of fractal analysis to investigate myoelectric fatigue, it is crucial to establish the interdependence between fractal dimension and muscle contraction intensity. We analyzed the behavior of fractal dimension, conduction velocity, mean frequency, and average rectified value in twenty-eight volunteers at nine levels of isometric force. sEMG was obtained using bidimensional arrays in the biceps brachii muscle. The values of fractal dimension and mean frequency increased with force unless a plateau was reached at 30% maximal voluntary contraction. Overall, our findings suggest that, above a certain level of force, the use of fractal dimension to evaluate the myoelectric manifestations of fatigue may be considered, regardless of muscle contraction intensity.

Noise and muscle contraction affecting vigilance task performance

The objective of this study was to determine the effects of muscle contraction intensity, neuromuscular fatigue, and noise on vigilance performance. Dependent variables included simple (reaction time and movement time) and complex (video game: Tetris) vigilance tasks (SVT and CVT respectively) and maximum voluntary contraction (MVC) force and activation. Vigilance tasks and MVC were randomly allocated to 5 minute blocks during a pre-test. Following the pre-test, the tests were again randomly allocated within three, 15 minute testing sessions over 65 minutes, while 1) being exposed to high (95 dB (A)) or low (53 dB (A)) levels of noise, and 2) performing muscle contractions at 20% and 5% of MVC, or no contractions. Ninety-five (95) dB (A) noise increased (p ≤ 0.01) SVT (reaction time and movement time combined) by 11.2% and decreased (p ≤ 0.01) CVT by 20%. Both 20% and 5% MVC impaired SVT and CVT to a similar extent, while no changes were seen with no contractions. Furthermore, neuromuscular fatigue had no apparent effect on vigilance task performance. These findings suggest that the distraction of noise and divided attention between muscle contraction and a vigilance task decreases performance.