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2020


A Gamified App that Helps People Overcome Self-Limiting Beliefs by Promoting Metacognition
A Gamified App that Helps People Overcome Self-Limiting Beliefs by Promoting Metacognition

Amo, V., Lieder, F.

SIG 8 Meets SIG 16, September 2020 (conference) Accepted

Abstract
Previous research has shown that approaching learning with a growth mindset is key for maintaining motivation and overcoming setbacks. Mindsets are systems of beliefs that people hold to be true. They influence a person's attitudes, thoughts, and emotions when they learn something new or encounter challenges. In clinical psychology, metareasoning (reflecting on one's mental processes) and meta-awareness (recognizing thoughts as mental events instead of equating them to reality) have proven effective for overcoming maladaptive thinking styles. Hence, they are potentially an effective method for overcoming self-limiting beliefs in other domains as well. However, the potential of integrating assisted metacognition into mindset interventions has not been explored yet. Here, we propose that guiding and training people on how to leverage metareasoning and meta-awareness for overcoming self-limiting beliefs can significantly enhance the effectiveness of mindset interventions. To test this hypothesis, we develop a gamified mobile application that guides and trains people to use metacognitive strategies based on Cognitive Restructuring (CR) and Acceptance Commitment Therapy (ACT) techniques. The application helps users to identify and overcome self-limiting beliefs by working with aversive emotions when they are triggered by fixed mindsets in real-life situations. Our app aims to help people sustain their motivation to learn when they face inner obstacles (e.g. anxiety, frustration, and demotivation). We expect the application to be an effective tool for helping people better understand and develop the metacognitive skills of emotion regulation and self-regulation that are needed to overcome self-limiting beliefs and develop growth mindsets.

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A gamified app that helps people overcome self-limiting beliefs by promoting metacognition [BibTex]


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How to navigate everyday distractions: Leveraging optimal feedback to train attention control

Wirzberger, M., Lado, A., Eckerstorfer, L., Oreshnikov, I., Passy, J., Stock, A., Shenhav, A., Lieder, F.

Annual Meeting of the Cognitive Science Society, July 2020 (conference)

Abstract
To stay focused on their chosen tasks, people have to inhibit distractions. The underlying attention control skills can improve through reinforcement learning, which can be accelerated by giving feedback. We applied the theory of metacognitive reinforcement learning to develop a training app that gives people optimal feedback on their attention control while they are working or studying. In an eight-day field experiment with 99 participants, we investigated the effect of this training on people's productivity, sustained attention, and self-control. Compared to a control condition without feedback, we found that participants receiving optimal feedback learned to focus increasingly better (f = .08, p < .01) and achieved higher productivity scores (f = .19, p < .01) during the training. In addition, they evaluated their productivity more accurately (r = .12, p < .01). However, due to asymmetric attrition problems, these findings need to be taken with a grain of salt.

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How to navigate everyday distractions: Leveraging optimal feedback to train attention control DOI Project Page [BibTex]


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Leveraging Machine Learning to Automatically Derive Robust Planning Strategies from Biased Models of the Environment

Kemtur, A., Jain, Y. R., Mehta, A., Callaway, F., Consul, S., Stojcheski, J., Lieder, F.

CogSci 2020, July 2020, Anirudha Kemtur and Yash Raj Jain contributed equally to this publication. (conference)

Abstract
Teaching clever heuristics is a promising approach to improve decision-making. We can leverage machine learning to discover clever strategies automatically. Current methods require an accurate model of the decision problems people face in real life. But most models are misspecified because of limited information and cognitive biases. To address this problem we develop strategy discovery methods that are robust to model misspecification. Robustness is achieved by model-ing model-misspecification and handling uncertainty about the real-world according to Bayesian inference. We translate our methods into an intelligent tutor that automatically discovers and teaches robust planning strategies. Our robust cognitive tutor significantly improved human decision-making when the model was so biased that conventional cognitive tutors were no longer effective. These findings highlight that our robust strategy discovery methods are a significant step towards leveraging artificial intelligence to improve human decision-making in the real world.

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Project Page [BibTex]

Project Page [BibTex]


Changes in Normal Force During Passive Dynamic Touch: Contact Mechanics and Perception
Changes in Normal Force During Passive Dynamic Touch: Contact Mechanics and Perception

Gueorguiev, D., Lambert, J., Thonnard, J., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium (HAPTICS), pages: 746-752, Washington, USA, March 2020 (inproceedings)

Abstract
Using a force-controlled robotic platform, we investigated the contact mechanics and psychophysical responses induced by negative and positive modulations in normal force during passive dynamic touch. In the natural state of the finger, the applied normal force modulation induces a correlated change in the tangential force. In a second condition, we applied talcum powder to the fingerpad, which induced a significant modification in the slope of the correlated tangential change. In both conditions, the same ten participants had to detect the interval that contained a decrease or an increase in the pre-stimulation normal force of 1 N. In the natural state, the 75% just noticeable difference for this task was found to be a ratio of 0.19 and 0.18 for decreases and increases, respectively. With talcum powder on the fingerpad, the normal force thresholds remained stable, following the Weber law of constant just noticeable differences, while the tangential force thresholds changed in the same way as the correlation slopes. This result suggests that participants predominantly relied on the normal force changes to perform the detection task. In addition, participants were asked to report whether the force decreased or increased. Their performance was generally poor at this second task even for above-threshold changes. However, their accuracy slightly improved with the talcum powder, which might be due to the reduced finger-surface friction.

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DOI [BibTex]

DOI [BibTex]


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ACTrain: Ein KI-basiertes Aufmerksamkeitstraining für die Wissensarbeit [ACTrain: An AI-based attention training for knowledge work]

Wirzberger, M., Oreshnikov, I., Passy, J., Lado, A., Shenhav, A., Lieder, F.

66th Spring Conference of the German Ergonomics Society, 2020 (conference)

Abstract
Unser digitales Zeitalter lebt von Informationen und stellt unsere begrenzte Verarbeitungskapazität damit täglich auf die Probe. Gerade in der Wissensarbeit haben ständige Ablenkungen erhebliche Leistungseinbußen zur Folge. Unsere intelligente Anwendung ACTrain setzt genau an dieser Stelle an und verwandelt Computertätigkeiten in eine Trainingshalle für den Geist. Feedback auf Basis maschineller Lernverfahren zeigt anschaulich den Wert auf, sich nicht von einer selbst gewählten Aufgabe ablenken zu lassen. Diese metakognitive Einsicht soll zum Durchhalten motivieren und das zugrunde liegende Fertigkeitsniveau der Aufmerksamkeitskontrolle stärken. In laufenden Feldexperimenten untersuchen wir die Frage, ob das Training mit diesem optimalen Feedback die Aufmerksamkeits- und Selbstkontrollfertigkeiten im Vergleich zu einer Kontrollgruppe ohne Feedback verbessern kann.

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link (url) Project Page [BibTex]

2019


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Deep Neural Network Approach in Electrical Impedance Tomography-Based Real-Time Soft Tactile Sensor

Park, H., Lee, H., Park, K., Mo, S., Kim, J.

In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 7447-7452, Macau, China, November 2019 (inproceedings)

Abstract
Recently, a whole-body tactile sensing have emerged in robotics for safe human-robot interaction. A key issue in the whole-body tactile sensing is ensuring large-area manufacturability and high durability. To fulfill these requirements, a reconstruction method called electrical impedance tomography (EIT) was adopted in large-area tactile sensing. This method maps voltage measurements to conductivity distribution using only a few number of measurement electrodes. A common approach for the mapping is using a linearized model derived from the Maxwell's equation. This linearized model shows fast computation time and moderate robustness against measurement noise but reconstruction accuracy is limited. In this paper, we propose a novel nonlinear EIT algorithm through Deep Neural Network (DNN) approach to improve the reconstruction accuracy of EIT-based tactile sensors. The neural network architecture with rectified linear unit (ReLU) function ensured extremely low computational time (0.002 seconds) and nonlinear network structure which provides superior measurement accuracy. The DNN model was trained with dataset synthesized in simulation environment. To achieve the robustness against measurement noise, the training proceeded with additive Gaussian noise that estimated through actual measurement noise. For real sensor application, the trained DNN model was transferred to a conductive fabric-based soft tactile sensor. For validation, the reconstruction error and noise robustness were mainly compared using conventional linearized model and proposed approach in simulation environment. As a demonstration, the tactile sensor equipped with the trained DNN model is presented for a contact force estimation.

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DOI [BibTex]

2019


DOI [BibTex]


How do people learn how to plan?
How do people learn how to plan?

Jain, Y. R., Gupta, S., Rakesh, V., Dayan, P., Callaway, F., Lieder, F.

Conference on Cognitive Computational Neuroscience, September 2019 (conference)

Abstract
How does the brain learn how to plan? We reverse-engineer people's underlying learning mechanisms by combining rational process models of cognitive plasticity with recently developed empirical methods that allow us to trace the temporal evolution of people's planning strategies. We find that our Learned Value of Computation model (LVOC) accurately captures people's average learning curve. However, there were also substantial individual differences in metacognitive learning that are best understood in terms of multiple different learning mechanisms-including strategy selection learning. Furthermore, we observed that LVOC could not fully capture people's ability to adaptively decide when to stop planning. We successfully extended the LVOC model to address these discrepancies. Our models broadly capture people's ability to improve their decision mechanisms and represent a significant step towards reverse-engineering how the brain learns increasingly effective cognitive strategies through its interaction with the environment.

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How do people learn to plan? How do people learn to plan? [BibTex]

How do people learn to plan? How do people learn to plan? [BibTex]


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Testing Computational Models of Goal Pursuit

Mohnert, F., Tosic, M., Lieder, F.

CCN2019, September 2019 (conference)

Abstract
Goals are essential to human cognition and behavior. But how do we pursue them? To address this question, we model how capacity limits on planning and attention shape the computational mechanisms of human goal pursuit. We test the predictions of a simple model based on previous theories in a behavioral experiment. The results show that to fully capture how people pursue their goals it is critical to account for people’s limited attention in addition to their limited planning. Our findings elucidate the cognitive constraints that shape human goal pursuit and point to an improved model of human goal pursuit that can reliably predict which goals a person will achieve and which goals they will struggle to pursue effectively.

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link (url) DOI Project Page [BibTex]


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Measuring How People Learn How to Plan

Jain, Y. R., Callaway, F., Lieder, F.

Proceedings 41st Annual Meeting of the Cognitive Science Society, pages: 1956-1962, CogSci2019, 41st Annual Meeting of the Cognitive Science Society, July 2019 (conference)

Abstract
The human mind has an unparalleled ability to acquire complex cognitive skills, discover new strategies, and refine its ways of thinking and decision-making; these phenomena are collectively known as cognitive plasticity. One important manifestation of cognitive plasticity is learning to make better–more far-sighted–decisions via planning. A serious obstacle to studying how people learn how to plan is that cognitive plasticity is even more difficult to observe than cognitive strategies are. To address this problem, we develop a computational microscope for measuring cognitive plasticity and validate it on simulated and empirical data. Our approach employs a process tracing paradigm recording signatures of human planning and how they change over time. We then invert a generative model of the recorded changes to infer the underlying cognitive plasticity. Our computational microscope measures cognitive plasticity significantly more accurately than simpler approaches, and it correctly detected the effect of an external manipulation known to promote cognitive plasticity. We illustrate how computational microscopes can be used to gain new insights into the time course of metacognitive learning and to test theories of cognitive development and hypotheses about the nature of cognitive plasticity. Future work will leverage our computational microscope to reverse-engineer the learning mechanisms enabling people to acquire complex cognitive skills such as planning and problem solving.

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Effect of Remote Masking on Detection of Electrovibration
Effect of Remote Masking on Detection of Electrovibration

Jamalzadeh, M., Güçlü, B., Vardar, Y., Basdogan, C.

In Proceedings of the IEEE World Haptics Conference (WHC), pages: 229-234, Tokyo, Japan, July 2019 (inproceedings)

Abstract
Masking has been used to study human perception of tactile stimuli, including those created on haptic touch screens. Earlier studies have investigated the effect of in-site masking on tactile perception of electrovibration. In this study, we investigated whether it is possible to change detection threshold of electrovibration at fingertip of index finger via remote masking, i.e. by applying a (mechanical) vibrotactile stimulus on the proximal phalanx of the same finger. The masking stimuli were generated by a voice coil (Haptuator). For eight participants, we first measured the detection thresholds for electrovibration at the fingertip and for vibrotactile stimuli at the proximal phalanx. Then, the vibrations on the skin were measured at four different locations on the index finger of subjects to investigate how the mechanical masking stimulus propagated as the masking level was varied. Finally, electrovibration thresholds measured in the presence of vibrotactile masking stimuli. Our results show that vibrotactile masking stimuli generated sub-threshold vibrations around fingertip, and hence did not mechanically interfere with the electrovibration stimulus. However, there was a clear psychophysical masking effect due to central neural processes. Electrovibration absolute threshold increased approximately 0.19 dB for each dB increase in the masking level.

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DOI [BibTex]

DOI [BibTex]


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Extending Rationality

Pothos, E. M., Busemeyer, J. R., Pleskac, T., Yearsley, J. M., Tenenbaum, J. B., Goodman, N. D., Tessler, M. H., Griffiths, T. L., Lieder, F., Hertwig, R., Pachur, T., Leuker, C., Shiffrin, R. M.

Proceedings of the 41st Annual Conference of the Cognitive Science Society, pages: 39-40, CogSci 2019, July 2019 (conference)

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Proceedings of the 41st Annual Conference of the Cognitive Science Society [BibTex]

Proceedings of the 41st Annual Conference of the Cognitive Science Society [BibTex]


How should we incentivize learning? An optimal feedback mechanism for educational games and online courses
How should we incentivize learning? An optimal feedback mechanism for educational games and online courses

Xu, L., Wirzberger, M., Lieder, F.

41st Annual Meeting of the Cognitive Science Society, July 2019 (conference)

Abstract
Online courses offer much-needed opportunities for lifelong self-directed learning, but people rarely follow through on their noble intentions to complete them. To increase student retention educational software often uses game elements to motivate students to engage in and persist in learning activities. However, gamification only works when it is done properly, and there is currently no principled method that educational software could use to achieve this. We develop a principled feedback mechanism for encouraging good study choices and persistence in self-directed learning environments. Rather than giving performance feedback, our method rewards the learner's efforts with optimal brain points that convey the value of practice. To derive these optimal brain points, we applied the theory of optimal gamification to a mathematical model of skill acquisition. In contrast to hand-designed incentive structures, optimal brain points are constructed in such a way that the incentive system cannot be gamed. Evaluating our method in a behavioral experiment, we find that optimal brain points significantly increased the proportion of participants who instead of exploiting an inefficient skill they already knew-attempted to learn a difficult but more efficient skill, persisted through failure, and succeeded to master the new skill. Our method provides a principled approach to designing incentive structures and feedback mechanisms for educational games and online courses. We are optimistic that optimal brain points will prove useful for increasing student retention and helping people overcome the motivational obstacles that stand in the way of self-directed lifelong learning.

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link (url) Project Page [BibTex]


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What’s in the Adaptive Toolbox and How Do People Choose From It? Rational Models of Strategy Selection in Risky Choice

Mohnert, F., Pachur, T., Lieder, F.

41st Annual Meeting of the Cognitive Science Society, July 2019 (conference)

Abstract
Although process data indicates that people often rely on various (often heuristic) strategies to choose between risky options, our models of heuristics cannot predict people's choices very accurately. To address this challenge, it has been proposed that people adaptively choose from a toolbox of simple strategies. But which strategies are contained in this toolbox? And how do people decide when to use which decision strategy? Here, we develop a model according to which each person selects decisions strategies rationally from their personal toolbox; our model allows one to infer which strategies are contained in the cognitive toolbox of an individual decision-maker and specifies when she will use which strategy. Using cross-validation on an empirical data set, we find that this rational model of strategy selection from a personal adaptive toolbox predicts people's choices better than any single strategy (even when it is allowed to vary across participants) and better than previously proposed toolbox models. Our model comparisons show that both inferring the toolbox and rational strategy selection are critical for accurately predicting people's risky choices. Furthermore, our model-based data analysis reveals considerable individual differences in the set of strategies people are equipped with and how they choose among them; these individual differences could partly explain why some people make better choices than others. These findings represent an important step towards a complete formalization of the notion that people select their cognitive strategies from a personal adaptive toolbox.

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link (url) [BibTex]


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Measuring How People Learn How to Plan

Jain, Y. R., Callaway, F., Lieder, F.

pages: 357-361, RLDM 2019, July 2019 (conference)

Abstract
The human mind has an unparalleled ability to acquire complex cognitive skills, discover new strategies, and refine its ways of thinking and decision-making; these phenomena are collectively known as cognitive plasticity. One important manifestation of cognitive plasticity is learning to make better – more far-sighted – decisions via planning. A serious obstacle to studying how people learn how to plan is that cognitive plasticity is even more difficult to observe than cognitive strategies are. To address this problem, we develop a computational microscope for measuring cognitive plasticity and validate it on simulated and empirical data. Our approach employs a process tracing paradigm recording signatures of human planning and how they change over time. We then invert a generative model of the recorded changes to infer the underlying cognitive plasticity. Our computational microscope measures cognitive plasticity significantly more accurately than simpler approaches, and it correctly detected the effect of an external manipulation known to promote cognitive plasticity. We illustrate how computational microscopes can be used to gain new insights into the time course of metacognitive learning and to test theories of cognitive development and hypotheses about the nature of cognitive plasticity. Future work will leverage our computational microscope to reverse-engineer the learning mechanisms enabling people to acquire complex cognitive skills such as planning and problem solving.

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link (url) [BibTex]

link (url) [BibTex]


Objective and Subjective Assessment of Algorithms for Reducing Three-Axis Vibrations to One-Axis Vibrations
Objective and Subjective Assessment of Algorithms for Reducing Three-Axis Vibrations to One-Axis Vibrations

Park, G., Kuchenbecker, K. J.

In Proceedings of the IEEE World Haptics Conference, pages: 467-472, July 2019 (inproceedings)

Abstract
A typical approach to creating realistic vibrotactile feedback is reducing 3D vibrations recorded by an accelerometer to 1D signals that can be played back on a haptic actuator, but some of the information is often lost in this dimensional reduction process. This paper describes seven representative algorithms and proposes four metrics based on the spectral match, the temporal match, and the average value and the variability of them across 3D rotations. These four performance metrics were applied to four texture recordings, and the method utilizing the discrete fourier transform (DFT) was found to be the best regardless of the sensing axis. We also recruited 16 participants to assess the perceptual similarity achieved by each algorithm in real time. We found the four metrics correlated well with the subjectively rated similarities for the six dimensional reduction algorithms, with the exception of taking the 3D vector magnitude, which was perceived to be good despite its low spectral and temporal match metrics.

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DOI [BibTex]

DOI [BibTex]


Fingertip Interaction Metrics Correlate with Visual and Haptic Perception of Real Surfaces
Fingertip Interaction Metrics Correlate with Visual and Haptic Perception of Real Surfaces

Vardar, Y., Wallraven, C., Kuchenbecker, K. J.

In Proceedings of the IEEE World Haptics Conference (WHC), pages: 395-400, Tokyo, Japan, July 2019 (inproceedings)

Abstract
Both vision and touch contribute to the perception of real surfaces. Although there have been many studies on the individual contributions of each sense, it is still unclear how each modality’s information is processed and integrated. To fill this gap, we investigated the similarity of visual and haptic perceptual spaces, as well as how well they each correlate with fingertip interaction metrics. Twenty participants interacted with ten different surfaces from the Penn Haptic Texture Toolkit by either looking at or touching them and judged their similarity in pairs. By analyzing the resulting similarity ratings using multi-dimensional scaling (MDS), we found that surfaces are similarly organized within the three-dimensional perceptual spaces of both modalities. Also, between-participant correlations were significantly higher in the haptic condition. In a separate experiment, we obtained the contact forces and accelerations acting on one finger interacting with each surface in a controlled way. We analyzed the collected fingertip interaction data in both the time and frequency domains. Our results suggest that the three perceptual dimensions for each modality can be represented by roughness/smoothness, hardness/softness, and friction, and that these dimensions can be estimated by surface vibration power, tap spectral centroid, and kinetic friction coefficient, respectively.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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A Cognitive Tutor for Helping People Overcome Present Bias

Lieder, F., Callaway, F., Jain, Y. R., Krueger, P. M., Das, P., Gul, S., Griffiths, T. L.

RLDM 2019, July 2019, Falk Lieder and Frederick Callaway contributed equally to this publication. (conference)

Abstract
People's reliance on suboptimal heuristics gives rise to a plethora of cognitive biases in decision-making including the present bias, which denotes people's tendency to be overly swayed by an action's immediate costs/benefits rather than its more important long-term consequences. One approach to helping people overcome such biases is to teach them better decision strategies. But which strategies should we teach them? And how can we teach them effectively? Here, we leverage an automatic method for discovering rational heuristics and insights into how people acquire cognitive skills to develop an intelligent tutor that teaches people how to make better decisions. As a proof of concept, we derive the optimal planning strategy for a simple model of situations where people fall prey to the present bias. Our cognitive tutor teaches people this optimal planning strategy by giving them metacognitive feedback on how they plan in a 3-step sequential decision-making task. Our tutor's feedback is designed to maximally accelerate people's metacognitive reinforcement learning towards the optimal planning strategy. A series of four experiments confirmed that training with the cognitive tutor significantly reduced present bias and improved people's decision-making competency: Experiment 1 demonstrated that the cognitive tutor's feedback can help participants discover far-sighted planning strategies. Experiment 2 found that this training effect transfers to more complex environments. Experiment 3 found that these transfer effects are retained for at least 24 hours after the training. Finally, Experiment 4 found that practicing with the cognitive tutor can have additional benefits over being told the strategy in words. The results suggest that promoting metacognitive reinforcement learning with optimal feedback is a promising approach to improving the human mind.

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DOI [BibTex]

DOI [BibTex]


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Introducing the Decision Advisor: A simple online tool that helps people overcome cognitive biases and experience less regret in real-life decisions

lawama, G., Greenberg, S., Moore, D., Lieder, F.

40th Annual Meeting of the Society for Judgement and Decision Making, June 2019 (conference)

Abstract
Cognitive biases shape many decisions people come to regret. To help people overcome these biases, Clear-erThinking.org developed a free online tool, called the Decision Advisor (https://programs.clearerthinking.org/decisionmaker.html). The Decision Advisor assists people in big real-life decisions by prompting them to generate more alternatives, guiding them to evaluate their alternatives according to principles of decision analysis, and educates them about pertinent biases while they are making their decision. In a within-subjects experiment, 99 participants reported significantly fewer biases and less regret for a decision supported by the Decision Advisor than for a previous unassisted decision.

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DOI [BibTex]

DOI [BibTex]


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The Goal Characteristics (GC) questionannaire: A comprehensive measure for goals’ content, attainability, interestingness, and usefulness

Iwama, G., Wirzberger, M., Lieder, F.

40th Annual Meeting of the Society for Judgement and Decision Making, June 2019 (conference)

Abstract
Many studies have investigated how goal characteristics affect goal achievement. However, most of them considered only a small number of characteristics and the psychometric properties of their measures remains unclear. To overcome these limitations, we developed and validated a comprehensive questionnaire of goal characteristics with four subscales - measuring the goal’s content, attainability, interestingness, and usefulness respectively. 590 participants completed the questionnaire online. A confirmatory factor analysis supported the four subscales and their structure. The GC questionnaire (https://osf.io/qfhup) can be easily applied to investigate goal setting, pursuit and adjustment in a wide range of contexts.

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DOI [BibTex]


Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design
Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design

Seifi, H., Fazlollahi, F., Oppermann, M., Sastrillo, J. A., Ip, J., Agrawal, A., Park, G., Kuchenbecker, K. J., MacLean, K. E.

In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Glasgow, Scotland, May 2019 (inproceedings)

Abstract
Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, experience designers are rarely engineers, and 30 years of haptic inventions are buried in a fragmented literature that describes devices mechanically rather than by potential purpose. We conceived of Haptipedia to unlock this trove of examples: Haptipedia presents a device corpus for exploration through metadata that matter to both device and experience designers. It is a taxonomy of device attributes that go beyond physical description to capture potential utility, applied to a growing database of 105 grounded force-feedback devices, and accessed through a public visualization that links utility to morphology. Haptipedia's design was driven by both systematic review of the haptic device literature and rich input from diverse haptic designers. We describe Haptipedia's reception (including hopes it will redefine device reporting standards) and our plans for its sustainability through community participation.

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Project Page [BibTex]

Project Page [BibTex]


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Internal Array Electrodes Improve the Spatial Resolution of Soft Tactile Sensors Based on Electrical Resistance Tomography

Lee, H., Park, K., Kim, J., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5411-5417, Montreal, Canada, May 2019, Hyosang Lee and Kyungseo Park contributed equally to this publication (inproceedings)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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A Clustering Approach to Categorizing 7 Degree-of-Freedom Arm Motions during Activities of Daily Living

Gloumakov, Y., Spiers, A. J., Dollar, A. M.

In Proceedings of the International Conference on Robotics and Automation (ICRA), pages: 7214-7220, Montreal, Canada, May 2019 (inproceedings)

Abstract
In this paper we present a novel method of categorizing naturalistic human arm motions during activities of daily living using clustering techniques. While many current approaches attempt to define all arm motions using heuristic interpretation, or a combination of several abstract motion primitives, our unsupervised approach generates a hierarchical description of natural human motion with well recognized groups. Reliable recommendation of a subset of motions for task achievement is beneficial to various fields, such as robotic and semi-autonomous prosthetic device applications. The proposed method makes use of well-known techniques such as dynamic time warping (DTW) to obtain a divergence measure between motion segments, DTW barycenter averaging (DBA) to get a motion average, and Ward's distance criterion to build the hierarchical tree. The clusters that emerge summarize the variety of recorded motions into the following general tasks: reach-to-front, transfer-box, drinking from vessel, on-table motion, turning a key or door knob, and reach-to-back pocket. The clustering methodology is justified by comparing against an alternative measure of divergence using Bezier coefficients and K-medoids clustering.

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DOI [BibTex]

DOI [BibTex]


Improving Haptic Adjective Recognition with Unsupervised Feature Learning
Improving Haptic Adjective Recognition with Unsupervised Feature Learning

Richardson, B. A., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 3804-3810, Montreal, Canada, May 2019 (inproceedings)

Abstract
Humans can form an impression of how a new object feels simply by touching its surfaces with the densely innervated skin of the fingertips. Many haptics researchers have recently been working to endow robots with similar levels of haptic intelligence, but these efforts almost always employ hand-crafted features, which are brittle, and concrete tasks, such as object recognition. We applied unsupervised feature learning methods, specifically K-SVD and Spatio-Temporal Hierarchical Matching Pursuit (ST-HMP), to rich multi-modal haptic data from a diverse dataset. We then tested the learned features on 19 more abstract binary classification tasks that center on haptic adjectives such as smooth and squishy. The learned features proved superior to traditional hand-crafted features by a large margin, almost doubling the average F1 score across all adjectives. Additionally, particular exploratory procedures (EPs) and sensor channels were found to support perception of certain haptic adjectives, underlining the need for diverse interactions and multi-modal haptic data.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


A Novel Texture Rendering Approach for Electrostatic Displays
A Novel Texture Rendering Approach for Electrostatic Displays

Fiedler, T., Vardar, Y.

In Proceedings of International Workshop on Haptic and Audio Interaction Design (HAID), Lille, France, March 2019 (inproceedings)

Abstract
Generating realistic texture feelings on tactile displays using data-driven methods has attracted a lot of interest in the last decade. However, the need for large data storages and transmission rates complicates the use of these methods for the future commercial displays. In this paper, we propose a new texture rendering approach which can compress the texture data signicantly for electrostatic displays. Using three sample surfaces, we first explain how to record, analyze and compress the texture data, and render them on a touchscreen. Then, through psychophysical experiments conducted with nineteen participants, we show that the textures can be reproduced by a signicantly less number of frequency components than the ones in the original signal without inducing perceptual degradation. Moreover, our results indicate that the possible degree of compression is affected by the surface properties.

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Fiedler19-HAID-Electrostatic [BibTex]

Fiedler19-HAID-Electrostatic [BibTex]


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Remediating Cognitive Decline with Cognitive Tutors

Das, P., Callaway, F., Griffiths, T. L., Lieder, F.

RLDM 2019, 2019 (conference)

Abstract
As people age, their cognitive abilities tend to deteriorate, including their ability to make complex plans. To remediate this cognitive decline, many commercial brain training programs target basic cognitive capacities, such as working memory. We have recently developed an alternative approach: intelligent tutors that teach people cognitive strategies for making the best possible use of their limited cognitive resources. Here, we apply this approach to improve older adults' planning skills. In a process-tracing experiment we found that the decline in planning performance may be partly because older adults use less effective planning strategies. We also found that, with practice, both older and younger adults learned more effective planning strategies from experience. But despite these gains there was still room for improvement-especially for older people. In a second experiment, we let older and younger adults train their planning skills with an intelligent cognitive tutor that teaches optimal planning strategies via metacognitive feedback. We found that practicing planning with this intelligent tutor allowed older adults to catch up to their younger counterparts. These findings suggest that intelligent tutors that teach clever cognitive strategies can help aging decision-makers stay sharp.

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DOI [BibTex]

DOI [BibTex]

2016


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Qualitative User Reactions to a Hand-Clapping Humanoid Robot

Fitter, N. T., Kuchenbecker, K. J.

In Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings, 9979, pages: 317-327, Lecture Notes in Artificial Intelligence, Springer International Publishing, November 2016, Oral presentation given by Fitter (inproceedings)

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[BibTex]

2016


[BibTex]


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Designing and Assessing Expressive Open-Source Faces for the Baxter Robot

Fitter, N. T., Kuchenbecker, K. J.

In Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings, 9979, pages: 340-350, Lecture Notes in Artificial Intelligence, Springer International Publishing, November 2016, Oral presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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Rhythmic Timing in Playful Human-Robot Social Motor Coordination

Fitter, N. T., Hawkes, D. T., Kuchenbecker, K. J.

In Social Robotics: 8th International Conference, ICSR 2016, Kansas City, MO, USA, November 1-3, 2016 Proceedings, 9979, pages: 296-305, Lecture Notes in Artificial Intelligence, Springer International Publishing, November 2016, Oral presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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Using IMU Data to Demonstrate Hand-Clapping Games to a Robot

Fitter, N. T., Kuchenbecker, K. J.

In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 851 - 856, October 2016, Interactive presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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ProtonPack: A Visuo-Haptic Data Acquisition System for Robotic Learning of Surface Properties

Burka, A., Hu, S., Helgeson, S., Krishnan, S., Gao, Y., Hendricks, L. A., Darrell, T., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages: 58-65, 2016, Oral presentation given by Burka (inproceedings)

hi

Project Page [BibTex]

Project Page [BibTex]


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Equipping the Baxter Robot with Human-Inspired Hand-Clapping Skills

Fitter, N. T., Kuchenbecker, K. J.

In Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pages: 105-112, 2016 (inproceedings)

hi

[BibTex]

[BibTex]


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Comparison of vibro-acoustic performance metrics in the design and optimization of stiffened composite fuselages

Serhat, G., Basdogan, I.

In Proceedings of International Congress and Exposition of Noise Control Engineering (INTER-NOISE), Hamburg, Germany, August 2016 (inproceedings)

Abstract
In this paper, a comparison of preliminary design methodologies for optimization of stiffened, fiber-reinforced composite fuselages for vibro-acoustic requirements is presented. Fuselage stiffness properties are modelled using lamination parameters and their effect on the vibro-acoustic performance is investigated using two different approaches. First method, only considers the structural model in order to explore the effect of design variables on fuselage vibrations. The simplified estimation of the acoustic behavior without considering fluid-structure interaction brings certain advantages such as reduced modelling effort and computational cost. In this case, the performance metric is chosen as equivalent radiated power (ERP) which is a well-known criterion in the prediction of structure-born noise. Second method, utilizes coupled vibro-acoustic models to predict the sound pressure levels (SPL) inside the fuselage. ERP is calculated both for bay panels and fuselage section and then compared with the SPL results. The response surfaces of each metric are determined as a function of lamination parameters and their overall difference is quantified. ERP approach proves its merit provided that a sufficiently accurate model is used. The results demonstrate the importance of the simplifications made in the modelling and the selection of analysis approach in vibro-acoustic design of fuselages.

hi

[BibTex]

[BibTex]


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Reproducing a Laser Pointer Dot on a Secondary Projected Screen

Hu, S., Kuchenbecker, K. J.

In Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pages: 1645-1650, 2016, Oral presentation given by Hu (inproceedings)

hi

[BibTex]

[BibTex]


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Effect of Aspect Ratio and Boundary Conditions on the Eigenfrequency Optimization of Composite Panels Using Lamination Parameters

Serhat, G., Basdogan, I.

In Proceedings of the ASMO UK International Conference on Numerical Optimisation Methods for Engineering Design, pages: 160–168, Munich, Germany, July 2016 (inproceedings)

Abstract
Eigenfrequency optimization of laminated composite panels is a common engineering problem. This process mostly involves designing stiffness properties of the structure. Optimal results can differ significantly depending on the values of the model parameters and the metrics used for the optimization. Building the know-how on this matter is crucial for choosing the appropriate design methodologies as well as validation and justification of prospective results. In this paper, effects of aspect ratio and boundary conditions on eigenfrequency optimization of composite panels by altering stiffness properties are investigated. Lamination parameters are chosen as design variables which are used in the modeling of stiffness tensors. This technique enables representation of overall stiffness characteristics and provides a convex design space. Fundamental frequency and difference between fundamental and second natural frequencies are maximized as design objectives. Optimization studies incorporating different models and responses are performed. Optimal lamination parameters and response values are provided for each case and the effects of model parameters on the solutions are quantified. The results indicate that trends of the optima change for different aspect ratio ranges and boundary conditions. Moreover, convergence occurs beyond certain critical values of the model parameters which may cause an optimization study to be redundant.

hi

[BibTex]

[BibTex]


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Multi-objective optimization of stiffened, fiber-reinforced composite fuselages for mechanical and vibro-acoustic requirements

Serhat, G., Faria, T. G., Basdogan, I.

In Proceedings of AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Washington, USA, June 2016 (inproceedings)

Abstract
In this paper, a preliminary design methodology for optimization of stiffened, fiber-reinforced composite fuselages for combined mechanical and vibro-acoustic requirements is presented. Laminate stiffness distributions are represented using the method called lamination parameters which is known to provide a convex solution space. Single-objective and multi-objective optimization studies are carried out in order to find optimal stiffness distributions. Performance metrics for acoustical behavior are chosen as maximum fundamental frequency and minimum equivalent radiated power. The mechanical performance metric is chosen as the maximum stiffness. The results show that the presented methodology works effectively and it can be used to improve load-carrying and acoustical performances simultaneously.

hi

DOI [BibTex]

DOI [BibTex]


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Deep Learning for Tactile Understanding From Visual and Haptic Data

Gao, Y., Hendricks, L. A., Kuchenbecker, K. J., Darrell, T.

In Proceedings of the IEEE International Conference on Robotics and Automation, pages: 536-543, May 2016, Oral presentation given by Gao (inproceedings)

hi

[BibTex]

[BibTex]


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Robust Tactile Perception of Artificial Tumors Using Pairwise Comparisons of Sensor Array Readings

Hui, J. C. T., Block, A. E., Taylor, C. J., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium, pages: 305-312, Philadelphia, Pennsylvania, USA, April 2016, Oral presentation given by Hui (inproceedings)

hi

[BibTex]

[BibTex]


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Data-Driven Comparison of Four Cutaneous Displays for Pinching Palpation in Robotic Surgery

Brown, J. D., Ibrahim, M., Chase, E. D. Z., Pacchierotti, C., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium, pages: 147-154, Philadelphia, Pennsylvania, USA, April 2016, Oral presentation given by Brown (inproceedings)

hi

[BibTex]

[BibTex]


Multisensory Robotic Therapy through Motion Capture and Imitation for Children with ASD
Multisensory Robotic Therapy through Motion Capture and Imitation for Children with ASD

Burns, R., Nizambad, S., Park, C. H., Jeon, M., Howard, A.

Proceedings of the American Society of Engineering Education, Mid-Atlantic Section, Spring Conference, April 2016 (conference)

Abstract
It is known that children with autism have difficulty with emotional communication. As the population of children with autism increases, it is crucial we create effective therapeutic programs that will improve their communication skills. We present an interactive robotic system that delivers emotional and social behaviors for multi­sensory therapy for children with autism spectrum disorders. Our framework includes emotion­-based robotic gestures and facial expressions, as well as tracking and understanding the child’s responses through Kinect motion capture.

hi

link (url) [BibTex]

link (url) [BibTex]


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Design and Implementation of a Visuo-Haptic Data Acquisition System for Robotic Learning of Surface Properties

Burka, A., Hu, S., Helgeson, S., Krishnan, S., Gao, Y., Hendricks, L. A., Darrell, T., Kuchenbecker, K. J.

In Proceedings of the IEEE Haptics Symposium, pages: 350-352, April 2016, Work-in-progress paper. Poster presentation given by Burka (inproceedings)

hi

Project Page [BibTex]

Project Page [BibTex]


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Psychophysical Power Optimization of Friction Modulation for Tactile Interfaces

Sednaoui, T., Vezzoli, E., Gueorguiev, D., Amberg, M., Chappaz, C., Lemaire-Semail, B.

In Haptics: Perception, Devices, Control, and Applications, pages: 354-362, Springer International Publishing, Cham, 2016 (inproceedings)

Abstract
Ultrasonic vibration and electrovibration can modulate the friction between a surface and a sliding finger. The power consumption of these devices is critical to their integration in modern mobile devices such as smartphones. This paper presents a simple control solution to reduce up to 68.8 {\%} this power consumption by taking advantage of the human perception limits.

hi

[BibTex]

[BibTex]


Effect of Waveform in Haptic Perception of Electrovibration on Touchscreens
Effect of Waveform in Haptic Perception of Electrovibration on Touchscreens

Vardar, Y., Güçlü, B., Basdogan, C.

In Haptics: Perception, Devices, Control, and Applications, pages: 190-203, Springer International Publishing, Cham, 2016 (inproceedings)

Abstract
The perceived intensity of electrovibration can be altered by modulating the amplitude, frequency, and waveform of the input voltage signal applied to the conductive layer of a touchscreen. Even though the effect of the first two has been already investigated for sinusoidal signals, we are not aware of any detailed study investigating the effect of the waveform on our haptic perception in the domain of electrovibration. This paper investigates how input voltage waveform affects our haptic perception of electrovibration on touchscreens. We conducted absolute detection experiments using square wave and sinusoidal input signals at seven fundamental frequencies (15, 30, 60, 120, 240, 480 and 1920 Hz). Experimental results depicted the well-known U-shaped tactile sensitivity across frequencies. However, the sensory thresholds were lower for the square wave than the sinusoidal wave at fundamental frequencies less than 60 Hz while they were similar at higher frequencies. Using an equivalent circuit model of a finger-touchscreen system, we show that the sensation difference between the waveforms at low fundamental frequencies can be explained by frequency-dependent electrical properties of human skin and the differential sensitivity of mechanoreceptor channels to individual frequency components in the electrostatic force. As a matter of fact, when the electrostatic force waveforms are analyzed in the frequency domain based on human vibrotactile sensitivity data from the literature [15], the electrovibration stimuli caused by square-wave input signals at all the tested frequencies in this study are found to be detected by the Pacinian psychophysical channel.

hi

vardar_eurohaptics_2016 [BibTex]

vardar_eurohaptics_2016 [BibTex]


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Helping people make better decisions using optimal gamification

Lieder, F., Griffiths, T. L.

In Proceedings of the 38th Annual Conference of the Cognitive Science Society, 2016 (inproceedings)

Abstract
Game elements like points and levels are a popular tool to nudge and engage students and customers. Yet, no theory can tell us which incentive structures work and how to design them. Here we connect the practice of gamification to the theory of reward shaping in reinforcement learning. We leverage this connection to develop a method for designing effective incentive structures and delineating when gamification will succeed from when it will fail. We evaluate our method in two behavioral experiments. The results of the first experiment demonstrate that incentive structures designed by our method help people make better, less short-sighted decisions and avoid the pitfalls of less principled approaches. The results of the second experiment illustrate that such incentive structures can be effectively implemented using game elements like points and badges. These results suggest that our method provides a principled way to leverage gamification to help people make better decisions.

re

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]

2015


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Assessing human-human therapy kinematics for retargeting to human-robot therapy

Johnson, M. J., Christopher, S. M., Mohan, M., Mendonca, R.

In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), Singapore, August 2015 (inproceedings)

Abstract
In this paper, we present experiments examining the accuracy of data collected from a Kinect sensor for capturing close interactive actions of a therapist with a patient during stroke rehabilitation. Our long-term goal is to map human-human interactions such as these patient-therapist ones onto human-robot interactions. In many robot interaction scenarios, the robot does not mimic interaction between two or more humans, which is a major part of stroke therapy. The Kinect works for functional tasks such as a reaching task where the interaction to be retargeted by the robot is minimal to none; though this data is not good for a functional task involving touching another person. We demonstrate that the noisy data from Kinect does not produce a system robust enough to be for remapping to a humanoid robot a therapit's movements when in contact with a person.

hi

DOI [BibTex]

2015


DOI [BibTex]


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Toward a large-scale visuo-haptic dataset for robotic learning

Burka, A., Hu, S., Krishnan, S., Kuchenbecker, K. J., Hendricks, L. A., Gao, Y., Darrell, T.

In Proc. CVPR Workshop on the Future of Datasets in Vision, 2015 (inproceedings)

hi

Project Page [BibTex]

Project Page [BibTex]


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Detecting Lumps in Simulated Tissue via Palpation with a BioTac

Hui, J., Block, A., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, 2015, Work-in-progress paper. Poster presentation given by Hui (inproceedings)

hi

[BibTex]

[BibTex]


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Analysis of the Instrument Vibrations and Contact Forces Caused by an Expert Robotic Surgeon Doing FRS Tasks

Brown, J. D., O’Brien, C., Miyasaka, K., Dumon, K. R., Kuchenbecker, K. J.

In Proc. Hamlyn Symposium on Medical Robotics, pages: 75-76, London, England, June 2015, Poster presentation given by Brown (inproceedings)

hi

[BibTex]

[BibTex]


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Should Haptic Texture Vibrations Respond to User Force and Speed?

Culbertson, H., Kuchenbecker, K. J.

In IEEE World Haptics Conference, pages: 106 - 112, Evanston, Illinois, USA, June 2015, Oral presentation given by Culbertson (inproceedings)

hi

[BibTex]

[BibTex]


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Enabling the Baxter Robot to Play Hand-Clapping Games

Fitter, N. T., Neuburger, M., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, June 2015, Work-in-progress paper. Poster presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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Using IMU Data to Teach a Robot Hand-Clapping Games

Fitter, N. T., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 353-355, April 2015, Work-in-progress paper. Poster presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]