Pengaruh Interaksi Sosial dan Efikasi Diri terhadap Kecerdasan Emosi (Survey pada Mahasiswa Pendidikan Akuntansi Upi)

Penelitian ini dilatarbelakangi oleh rendahnya sebagian mahasiswa Pendidikan Akuntansi berkaitan dengan kecerdasan emosi mahasiswa Pendidikan Akuntansi. Pentingnya mengkaji kecerdasan emosi mahasiswa, berkaitan dengan tujuan program studi Pendidikan Akuntansi yaitu mempersiapkan calon guru akuntansi menjelang PPL, dimana bukan hanya aspek kecerdasan intelgensi, namun kecerdasan emosi juga sangat penting dalam mempersiapkan mahasiswa terutama. Teori untuk membahas penelitian ini adalah kecerdasan Emosi dari Goleman, efikasi diri dari Bandura dan Interaksi sosial Tujuan penelitian ini adalah untuk mengkaji pengaruh interaksi sosial dan efikasi diri terhadap kecerdasan emosi. Metode penelitian menggunakan verifikatif dengan desain survey ekspalanatory. Populasi seluruh mahasiswa Pendidikan Akuntansi sebanyak dengan sampel 120 responden. Pengumpulan data dengan angket dan analisis data menggunakan analisis jalur (path analysis). Hasil penelitian menunjukkan bahwa interaksi sosial dan efikasi diri baik secara parsial maupun secara simultan berpengaruh positif terhadap kecerdasan emosi. Dengan Interaksi sosial sebagai faktor yang paling berpengaruh terhadap kecerdasan emosi. Berdasarkan analisis data, maka diperlukan peningkatan indikator yang masih rendah yaitu indikator kerjasama dalam variabel interaksi sosial dan perencanaan pengaturan diri dalam variabel efikasi diri

Evidence for a Time-Invariant Phase Variable in Human Ankle Control

Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-dependent feedback to accommodate perturbations. Two popular theories have been proposed for the underlying embodiment of phase in the human pattern generator: a time-dependent internal representation or a time-invariant feedback representation (i.e., reflex mechanisms). In either case the neuromuscular system must update or represent the phase of locomotor patterns based on the system state, which can include measurements of hundreds of variables. However, a much simpler representation of phase has emerged in recent designs for legged robots, which control joint patterns as functions of a single monotonic mechanical variable, termed a phase variable. We propose that human joint patterns may similarly depend on a physical phase variable, specifically the heel-to-toe movement of the Center of Pressure under the foot. We found that when the ankle is unexpectedly rotated to a position it would have encountered later in the step, the Center of Pressure also shifts forward to the corresponding later position, and the remaining portion of the gait pattern ensues. This phase shift suggests that the progression of the stance ankle is controlled by a biomechanical phase variable, motivating future investigations of phase variables in human locomotor control.United States Army Medical Research Acquisition Activity (USAMRAA grant W81XWH-09-2-0020)National Institute of Neurological Disorders and Stroke (U.S.) (NIH award number F31NS074687)Burroughs Wellcome Fund (Career Award at the Scientific Interface

Towards Biomimetic Virtual Constraint Control of a Powered Prosthetic Leg

Abstract-This brief presents a novel control strategy for a powered prosthetic ankle based on a biomimetic virtual constraint. We first derive a kinematic constraint for the "effective shape" of the human ankle-foot complex during locomotion. This shape characterizes ankle motion as a function of the Center of Pressure (COP)-the point on the foot sole where the resultant ground reaction force is imparted. Since the COP moves monotonically from heel to toe during steady walking, we adopt the COP as a mechanical representation of the gait cycle phase in an autonomous feedback controller. We show that our kinematic constraint can be enforced as a virtual constraint by an output linearizing controller that uses only feedback available to sensors onboard a prosthetic leg. Using simulations of a passive walking model with feet, we show that this novel controller exactly enforces the desired effective shape whereas a standard impedance (i.e., proportional-derivative) controller cannot. This work provides a single, biomimetic control law for the entire single-support period during robot-assisted locomotion

NON-BACKDRIVABLE SERIES ELASTIC ACTUATOR FOR USE IN A PROSTHETIC ELBOW

Commercially available prosthetic elbows have stiff actuators (motors) that are only capable of motion (position or velocity) control. In an attempt to mimic human physiology while accommodating prosthetic demands, a non-backdrivable motor has been created that is less stiff and capable of impedance control. Impedance control responds well to different environments and the presence of perturbations. Results have shown that this motor, though non-backdrivable to ensure sufficient battery supply, is still capable of exerting sufficient torque, speed, and frequency bandwidth to be useful in prosthetics. In the future, patients will be fit with this type of motor to examine if they objectively and subjectively perform better using this more physiologically appropriate prosthesis

Data from: Evaluating internal model strength and performance of myoelectric prosthesis control strategies

Ongoing developments in myoelectric prosthesis control have provided prosthesis users with an assortment of control strategies that vary in reliability and performance. Many studies have focused on improving performance by providing feedback to the user, but have overlooked the effect of this feedback on internal model development, which is key to improving long-term performance. In this work, the strength of internal models developed for two commonly used myoelectric control strategies: raw control with raw feedback (using a regression-based approach), and filtered control with filtered feedback (using a classifier-based approach), were evaluated using two psychometric measures: trial-by-trial adaptation and just-noticeable-difference. The performance of both strategies was also evaluated using a Schmidt’s style target acquisition task. Results obtained from 24 able-bodied subjects showed that although filtered control with filtered feedback had better short-term performance in path efficiency (p < 0.05), raw control with raw feedback resulted in stronger internal model development (p < 0.05), which may lead to better long-term performance. Despite inherent noise in the control signals of the regression controller, these findings suggest that rich feedback associated with regression control may be used to improve human understanding of the myoelectric control system