Louise Rosanna Manfredi

Complex design issues require a multi-disciplinary approach. Building an environment where students can work with experts from different fields can be incredibly beneficial to not only the students working to solve the problem but also for the intended user of their work. This approach was piloted in a Human Factors for Designers class at Syracuse University, centering on the topic of sensory processing disorder (SPD). Specifically, students focused on sensory processing in children with autism spectrum disorder (ASD) and how they can be over- or under-responsive to tactile, auditory, or visual stimuli. Five groups of three students enrolled in the industrial and interaction design program spent six weeks learning from a variety of experts who work on SPD, then employing their design and engineering skills to find solutions to existing problems. The specific research goal was to learn about the connection between sensory processing and behavior from a team of academic neuroscientists and local occupational therapists who support the children and their families. In addition to these experts, students spent time with the education director of a local science and technology museum to learn how the museum temporarily reworks exhibits to accommodate children and parents affected by SPD. Using this research as a foundation, students were required to design either a toy or a therapeutic device to solve a problem they had encountered. The toy was required to possess educational value, and the therapeutic device needed to offer a function that facilitated interaction between the parent and their child. A working physical prototype, presentation, and research portfolio were required deliverables. In addition to detailing the outcomes of the project, this paper discusses the merits and drawbacks of short timeframe multi-disciplinary teaching collaborations along with recommendations for further development.

To design a successful consumer product, a diverse team of experts from various disciplines is typically required. These disciplines bring unique insights into the product development process and can be key to creating innovative output. Working in these teams can be challenging, especially if technical language and ideal outcomes are not routinely communicated to the whole team. This work-in-progress paper examines an industry multi-disciplinary engineering design team. Specifically, this study investigates the communication channels between industrial design interns and an engineering team at an aerospace company in California. Members of this team ( ) were interviewed to record their experiences during this three-month project. At this initial research stage, methods of communication used, how effectively they communicated with each other, and what was learned about different design methodologies was captured. The purpose of this study was twofold as we sought to satisfy questions from the industrial and the academic perspectives. From the industrial viewpoint; what skills can industrial design bring to an engineering company to elevate its design practices, and academically, how might we prepare undergraduate engineers and industrial designers to work on these teams and facilitate an integrative approach to product development? A grounded theory approach was utilized to extract repeated ideas and themes from these interview transcripts which can be used in further studies of this nature to generate testable hypotheses. In addition to discussing the merits of this data analysis approach and the key insights that were gleaned, this work-in-progress paper provides recommendations to preempt unclear communication for newly formed multi-disciplinary teams.

Tactile information arising from mechanical interaction with the environment is first conveyed by the skin. Prior studies have shown that mechanical waves propagating in tissues carry significant tactile information far away from the region of contact. It is therefore important to determine whether it is appropriate to consider the skin to be a linear wave propagation medium since linearity would considerably simplify any analysis related to this phenomenon. For example, linearity would enable the application of the superposition principle, of the reciprocity principle, inter alia, even if the skin is considered to be anisotropic. The linearity assumption is important for the scientist interested in the physics of the tactile perception and it can also be surmised to be taken into account by the neural circuits processing tactile information. Such property would be important even if much of the other tactile physics, such as friction, are predominantly nonlinear. We found that indeed, the human fingertip skin could be considered to be a linear propagation medium, except in irregular regions such as the folds near the joints where linearity breaks down.

Sensory systems are designed to extract behaviorally relevant information from the environment. In seeking to understand a sensory system, it is important to understand the environment within which it operates. In the present study, we seek to characterize the natural scenes of tactile texture perception. During tactile exploration complex high-frequency vibrations are elicited in the fingertip skin, and these vibrations are thought to carry information about the surface texture of manipulated objects. How these texture-elicited vibrations depend on surface microgeometry and on the biomechanical properties of the fingertip skin itself remains to be elucidated. Here we record skin vibrations, using a laser-Doppler vibrometer, as various textured surfaces are scanned across the finger. We find that the frequency composition of elicited vibrations is texture specific and highly repeatable. In fact, textures can be classified with high accuracy on the basis of the vibrations they elicit in the skin. As might be expected, some aspects of surface microgeometry are directly reflected in the skin vibrations. However, texture vibrations are also determined in part by fingerprint geometry. This mechanism enhances textural features that are too small to be resolved spatially, given the limited spatial resolution of the neural signal. We conclude that it is impossible to understand the neural basis of texture perception without first characterizing the skin vibrations that drive neural responses, given the complex dependence of skin vibrations on both surface microgeometry and fingertip biomechanics.

Significance: Our exquisite tactile sensitivity to surface texture allows us to distinguish silk from satin or even good silk from cheap silk. We show that the tactile perception of natural textures relies on two neural mechanisms. Coarse textural features, for example, the individual elements of Braille, are represented in spatial patterns of activation across one population of mechanoreceptive afferents that densely innervate the fingertip skin. In contrast, our ability to discern fine textural features is mediated by the transduction and processing of vibrations produced in the skin during scanning. Indeed, two other populations of vibration-sensitive afferents produce temporally patterned responses to these vibrations, and spiking patterns in these afferent populations convey texture information and shape the way textures are perceived.

Tactile sensation is critical for effective object manipulation, but current prosthetic upper limbs make no provision for delivering somesthetic feedback to the user. For individuals who require use of prosthetic limbs, this lack of feedback transforms a mundane task into one that requires extreme concentration and effort. Although vibrotactile motors and sensory substitution devices can be used to convey gross sensations, a direct neural interface is required to provide detailed and intuitive sensory feedback. In light of this, we describe the implementation of a somatosensory prosthesis with which we elicit, through intracortical microstimulation (ICMS), percepts whose magnitude is graded according to the force exerted on the prosthetic finger. Specifically, the prosthesis consists of a sensorized finger, the force output of which is converted into a regime of ICMS delivered to primary somatosensory cortex through chronically implanted multi-electrode arrays. We show that the performance of animals (Rhesus macaques) on a tactile task is equivalent whether stimuli are delivered to the native finger or to the prosthetic finger.

Because tactile perception relies on the response of large populations of receptors distributed across the skin, we seek to characterize how a mechanical deformation of the skin at one location affects the skin at another. To this end, we introduce a novel non-contact method to characterize the surface waves produced in the skin under a variety of stimulation conditions. Specifically, we deliver vibrations to the fingertip using a vibratory actuator and measure, using a laser Doppler vibrometer, the surface waves at different distances from the locus of stimulation. First, we show that a vibration applied to the fingertip travels at least the length of the finger and that the rate at which it decays is dependent on stimulus frequency. Furthermore, the resonant frequency of the skin matches the frequency at which a subpopulation of afferents, namely Pacinian afferents, is most sensitive. We show that this skin resonance can lead to a two-fold increase in the strength of the response of a simulated afferent population. Second, the rate at which vibrations propagate across the skin is dependent on the stimulus frequency and plateaus at 7 m/s. The resulting delay in neural activation across locations does not substantially blur the temporal patterning in simulated populations of afferents for frequencies less than 200 Hz, which has important implications about how vibratory frequency is encoded in the responses of somatosensory neurons. Third, we show that, despite the dependence of decay rate and propagation speed on frequency, the waveform of a complex vibration is well preserved as it travels across the skin. Our results suggest, then, that the propagation of surface waves promotes the encoding of spectrally complex vibrations as the entire neural population is exposed to essentially the same stimulus. We also discuss the implications of our results for biomechanical models of the skin.