Role of arm reaching movement kinematics in friction perception at initial contact with smooth surfaces.

When manipulating objects, humans begin adjusting their grip force to friction within 100 ms of contact. During motor adaptation, subjects become aware of the slipperiness of touched surfaces. Previously, we have demonstrated that humans cannot perceive frictional differences when surfaces are brought in contact with an immobilised finger, but can do so when there is submillimeter lateral displacement or subjects actively make the contact movement.

How Tactile Afferents in the Human Fingerpad Encode Tangential Torques Associated with Manipulation: Are Monkeys Better than Us?

Dexterous object manipulation depends critically on information about forces normal and tangential to the fingerpads, and also on torque associated with object orientation at grip surfaces. We investigated how torque information is encoded by human tactile afferents in the fingerpads and compared them to 97 afferents recorded in monkeys ( = 3; 2 females) in our previous study. Human data included slowly-adapting Type-II (SA-II) afferents, which are absent in the glabrous skin of monkeys.

Submillimeter Lateral Displacement Enables Friction Sensing and Awareness of Surface Slipperiness.

Human tactile perception and motor control rely on the frictional estimates that stem from the deformation of the skin and slip events. However, it is not clear how exactly these mechanical events relate to the perception of friction. This study aims to quantify how minor lateral displacement and speed enables subjects to feel frictional differences.

Friction sensing mechanisms for perception and motor control: passive touch without sliding may not provide perceivable frictional information.

Perception of the frictional properties of a surface contributes to the multidimensional experience of exploring various materials; we slide our fingers over a surface to feel it. In contrast, during object manipulation, we grip objects without such intended exploratory movements. Given that we are aware of the slipperiness of objects or tools that are held in the hand, we investigated whether the initial contact between the fingertip skin and the surface of the object is sufficient to provide this consciously perceived frictional information.

A Biomimetic Approach toward Enhancing Angiogenesis: Recombinantly Expressed Domain V of Human Perlecan Is a Bioactive Molecule That Promotes Angiogenesis and Vascularization of Implanted Biomaterials.

Angiogenic therapy involving delivery of pro-angiogenic growth factors to stimulate new blood vessel formation in ischemic disease is promising but has seen limited clinical success due to issues associated with the need to deliver supra-physiological growth factor concentrations. Bio-inspired growth factor delivery utilizing the native growth factor signaling roles of the extracellular matrix proteoglycans has the potential to overcome many of the drawbacks of angiogenic therapy. In this study, the potential of the recombinantly expressed domain V (rDV) of human perlecan is investigated as a means of promoting growth factor signaling toward enhanced angiogenesis and vascularization of implanted biomaterials.

Estimating Lower Limb Kinematics Using a Reduced Wearable Sensor Count.

Goal: This paper presents an algorithm for accurately estimating pelvis, thigh, and shank kinematics during walking using only three wearable inertial sensors.

Methods: The algorithm makes novel use of a constrained Kalman filter (CKF). The algorithm iterates through the prediction (kinematic equation), measurement (pelvis position pseudo-measurements, zero velocity update, flat-floor assumption, and covariance limiter), and constraint update (formulation of hinged knee joints and ball-and-socket hip joints).

Detection of Atrial Fibrillation from RR Intervals and PQRST Morphology using a Neural Network Ensemble.

Early detection and discrimination of cardiac arrhythmia, atrial fibrillation (AF) in particular, is essential for timely intervention to improve patient outcomes. In this work, an algorithm was developed to classify ECG records as normal, AF, other arrhythmia, or too noisy to classify. This algorithm, which was an entry for the PhysioNet Computing in Cardiology Challenge 2017 (the Challenge), is described.

Single camera multi-view anthropometric measurement of human height and mid-upper arm circumference using linear regression.

Background: Manually measured anthropometric quantities are used in many applications including human malnutrition assessment. Training is required to collect anthropometric measurements manually, which is not ideal in resource-constrained environments. Photogrammetric methods have been gaining attention in recent years, due to the availability and affordability of digital cameras.

The Bayesian Decoding of Force Stimuli from Slowly Adapting Type I Fibers in Humans.

It is well known that signals encoded by mechanoreceptors facilitate precise object manipulation in humans. It is therefore of interest to study signals encoded by the mechanoreceptors because this will contribute further towards the understanding of fundamental sensory mechanisms that are responsible for coordinating force components during object manipulation. From a practical point of view, this may suggest strategies for designing sensory-controlled biomedical devices and robotic manipulators.

QRS Detection Algorithm for Telehealth Electrocardiogram Recordings.

Objective: QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a "UNSW" QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG.

An eight-legged tactile sensor to estimate coefficient of static friction.

It is well known that a tangential force larger than the maximum static friction force is required to initiate the sliding motion between two objects, which is governed by a material constant called the coefficient of static friction. Therefore, knowing the coefficient of static friction is of great importance for robot grippers which wish to maintain a stable and precise grip on an object during various manipulation tasks. Importantly, it is most useful if grippers can estimate the coefficient of static friction without having to explicitly explore the object first, such as lifting the object and reducing the grip force until it slips.

Decoding tactile afferent activity to obtain an estimate of instantaneous force and torque applied to the fingerpad.

Dexterous manipulation is not possible without sensory information about object properties and manipulative forces. Fundamental neuroscience has been unable to demonstrate how information about multiple stimulus parameters may be continuously extracted, concurrently, from a population of tactile afferents. This is the first study to demonstrate this, using spike trains recorded from tactile afferents innervating the monkey fingerpad.

Tactile afferents encode grip safety before slip for different frictions.

Adjustments to frictional forces are crucial to maintain a safe grip during precision object handling in both humans and robotic manipulators. The aim of this work was to investigate whether a population of human tactile afferents can provide information about the current tangential/normal force ratio expressed as the percentage of the critical load capacity - the tangential/normal force ratio at which the object would slip. A smooth stimulation surface was tested on the fingertip under three frictional conditions, with a 4 N normal force and a tangential force generated by motion in the ulnar or distal direction at a fixed speed.

Frequency-moment signatures: a method for automated seizure detection from scalp EEG.

Objectives: To investigate patient-specific automated epileptic seizure detection from scalp EEG using a new technique: frequency-moment signatures.

Methods: Signatures were calculated from 32s blocks of data of electrode differences from the right (RH) and left hemisphere (LH). Discrete Fourier transforms of 15 data subsets were calculated per block per hemisphere.

Decoding tactile sensation: multiple regression analysis of monkey fingertip afferent mechanoreceptor population responses.

How complex tactile sensations are encoded by populations of afferent mechanoreceptors is currently not well understood. While much is known about how individual afferents respond to prescribed stimuli, their behavior as a population distributed across the fingertip has not been well described. In this study, tactile afferent mechanoreceptors in monkey fingertips were mechanically stimulated, using a flat disc shaped probe, with several magnitudes of normal force (1.