Leanne Hirshfield's research while affiliated with University of Colorado Boulder and other places
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Publications (35)
Classroom orchestration requires teachers to concurrently manage multiple activities across multiple social levels (individual, group, and class) and under various constraints. Real-time dashboards can support teachers; however, designing actionable dashboards is a huge challenge. This paper describes a participatory design study to identify and in...
Intelligent agents are rapidly evolving from assistants into teammates as they perform increasingly complex tasks. Successful human-agent teams leverage the computational power and sensory capabilities of automated agents while keeping the human operator's expectation consistent with the agent's ability. This helps prevent over-reliance on and unde...
Predicting workload using physiological sensors has taken on a diffuse set of methods in recent years. However, the majority of these methods train models on small datasets, with small numbers of channel locations on the brain, limiting a models ability to transfer across participants, tasks, or experimental sessions. In this paper, we introduce a...
We investigate the effectiveness of robot-generated mixed reality gestures. Our findings demonstrate how these gestures increase user effectiveness by decreasing user response time, and that robots can pair long referring expressions with mixed reality gestures without cognitively overloading users.
We investigate the effectiveness of robot-generated mixed reality gestures. Our findings demonstrate how these gestures increase user effectiveness by decreasing user response time, and that robots can pair long referring expressions with mixed reality gestures without cognitively overloading users.
Studying the relationship between the brain and finger tapping motions can contribute towards an improved understanding of neuromuscular impairment. Furthermore, acquiring brain data signals non-intrusively during finger tapping exercises, and building a robust classification model can aid in the field of human computer interaction. In this paper,...
Objectives
This research aimed to examine the mechanisms of change associated with mindfulness-based interventions (MBI) and test the feasibility of using functional near-infrared spectroscopy (fNIRS) to objectively measure MBI-responsive neuro-cognitive functions impaired by stress and trauma: attentional control (AC), emotional regulation (ER), a...
We present the first experiment analyzing the effectiveness of robot-generated mixed reality gestures using real robotic and mixed reality hardware. Our findings demonstrate how these gestures increase user effectiveness by decreasing user response time during visual search tasks, and show that robots can safely pair longer, more natural referring...
In Human–Machine Teaming environments, it is important to identify potential performance drops due to cognitive overload. If identified correctly, they can help improve the performance of the human–machine system by offloading some tasks to less cognitively overloaded users. This can help prevent user error that can result in critical failures. Als...
In recent years, research involving the use of neurophysiological sensor streams to quantitatively measure and predict the level of mental workload experienced by an individual user has gained momentum as the complexity of the tasks operators have experienced in heavily computerized contexts has continued to expand. Despite the promising results fr...
Novice meditators often find it difficult to tune out external distractions which hinders their ability to engage in mindfulness practice. The problem is further exacerbated by stress and directed attention fatigue. Researchers and tech companies are experimenting with nature-inspired themes to improve the meditation session quality. In this paper,...
In the field of Human-Robot Interaction, researchers often techniques such as the Wizard-of-Oz paradigms in order to better study narrow scientific questions while carefully controlling robots’ capabilities unrelated to those questions, especially when those other capabilities are not yet easy to automate. However, those techniques often impose lim...
In this work, we present a novel and promising approach to autonomously detect different levels of simultaneous and spatiotemporal activity in multidimensional data. We introduce a new multilabeling technique, which assigns different labels to different regions of interest in the data, and thus, incorporates the spatial aspect. Each label is built...
This paper explores the tradeoffs between different types of mixed reality robotic communication under different levels of user work-load. We present the results of a within-subjects experiment in which we systematically and jointly vary robot communication style alongside level and type of cognitive load, and measure subsequent impacts on accuracy...
This within-subjects exploratory study examined users’ (N = 13) neurological responses to a racially-charged VR experience. The goals of the study are (1) to test a new method of assessing neural activity while users are experiencing VR using non-invasive functional near-infrared spectroscopy (fNIRS) device and VR headset, and (2) to compare activa...
We present a convolutional neural network- and long short-term memory-based method to classify the valence level of a computer user based on functional near infrared spectroscopy data. Convolutional neural networks are well suited for capturing the spatial characteristics of functional near infrared spectroscopy data. And long short-term memories a...
With terms like ‘fake news’ and ‘cyber attack’ dominating the news, skepticism toward the media and other online individuals has become a major facet of modern life. This paper views the way we process information during HCI through the lens of suspicion, a mentally taxing state that people enter before making a judgment about whether or not to tru...
Despite the importance that human error in the cyber domain has had in recent reports, cyber warfare research to date has largely focused on the effects of cyber attacks on the target computer system. In contrast, there is little empirical work on the role of human operators during cyber breaches. More specifically, there is a need to understand th...
Native advertising seeks to bypass consumer avoidance behaviour by integrating with sponsored content. While such advertisements are more likely to be seen and remembered, they may also increase viewer feelings of betrayal. Self-report surveys make it unclear when this sense of betrayal occurs, especially for applications of branded content, such a...
In this paper, we study the neural underpinnings relevant to user-centered web security through the lens of functional near-infrared spectroscopy (fNIRS). Specifically, we design and conduct an fNIRS study to pursue a thorough investigation of users' processing of legitimate vs. illegitimate and familiar vs. unfamiliar websites. We pinpoint the neu...
![Fig.7. Heart rate waveform [43] • RR interval: Time difference between...](profile/Danushka-Bandara-2/publication/304189912/figure/fig9/AS:667943721529368@1536261601883/Heart-rate-waveform-43-RR-interval-Time-difference-between-R-spikes-of-each_Q320.jpg)
We describe a method of achieving emotion classification using ECG and EDA data. There have been many studies conducted on usage of heart rate and EDA data to quantify the arousal level of a user [1–3]. Researchers have identified a connection between a person’s ECG data and the positivity or negativity of their emotional state [4]. The goal of thi...
Attempts have been made to evaluate people’s situational awareness (SA) in military and civilian contexts through subjective surveys, speed, and accuracy data acquired during SA target tasks. However, it is recognized in the SA domain that more systematic measurement is necessary to assess SA theories and applications. Recent advances in biomedical...
This article introduces the construct of suspicion to researchers in business and applied psychology, provides a literature-based definition of state suspicion and an initial self-report measure of that construct, and encourages research on this important topic. The construct of suspicion is under-researched in business and applied psychology, yet...
The Journal of Business and Psychology announces a special issue and call for papers entitled “Embedding the concept of suspicion in research on business and applied psychology.” A link to the associated invited article (Bobko et al., J Bus Psychol, doi:10.1007/s10869-014-9360-y, 2014b) is provided below. We seek both theoretical and empirical pape...
Humanity’s desire to enable machines to “understand” us drives research that seeks to uncover the mysteries of human beings and of their reactions. That is because a computer’s ability to correctly classify our emotions will lead to an enhanced experience for a user. Making use of the eye of the computer, a webcam, we can acquire human reaction dat...
There is limited literature on classifying user personality/learning style and other cross subject traits using brain activity patterns. In this paper we describe an experiment to classify a computer user’s’ personality type and learning style using their brain data acquired while they were conducting spatial/verbal tasks in front of a computer. Th...
We investigate creating a predictive model that increases accuracy in personality prediction of social media and social network site users through a multidisciplinary pilot analysis. We present a novel method for increasing personality prediction accuracy of Facebook users. We discuss an experiment that combines natural language processing and mach...
Objective:
The objective was to review and integrate available research about the construct of state-level suspicion as it appears in social science literatures and apply the resulting findings to information technology (IT) contexts.
Background:
Although the human factors literature is replete with articles about trust (and distrust) in automat...
Citations
... More generally, our findings follow prior work that support the idea that implicit measures like coherence between brain regions can be used to design, implement and control agents using adaptive automation (Akash et al., 2018;Kohn et al., 2021;Krueger and Wiese, 2021;Eloy et al., 2022). For example, Akash and colleagues have shown that data from the electroencephalogram (EEG) can assist in developing human trust sensors that can implicitly predict an operator's trust levels. ...
... Toward that goal, we propose a set of design recommendations and techniques that combine anthropomorphic and non-anthropomorphic virtual gestures based on the placement of the robot, user, and target object during an interaction. Our design recommendations were compiled by analyzing the relevant literature for design considerations, and highlighting factors that were reported to significantly influence either social perception or task efficiency [3], [7], [8], [9], [10]. We distil the findings into the following key factors: motivation of the interaction, a target's visibility, a target's salience, and a target's distance. ...
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... fNIRS has been used to works (CNN), the left finger, right finger, and foot-tapping tasks were differentiated with higher classification accuracy of 96.67%. In one of the recent studies, left and right index finger-tapping were distinguished with a different tapping frequency using multilabeling and deep learning [23]. Different labels were assigned to right and left finger-tapping with different tapping frequencies labels such as rest, 80 bpm, and 120 bpm. ...
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... Robotic Arms [21,25,27,33,51,59,79,105,133,136,140,153,182,262,270,282,285,325,326,341,354,358,372] Drones [15,58,76,96,114,171,261,332,382,436,450,451,475,482,494] Mobile Robots [53,91,112,163,169,177,191,197,209,210,212,221,263,305,328,346,370,407,418,445,467,468] Humanoid Robots [14,29,59,158,183,254,262,372,429,439,440] Vehicles [2,7,223,300,314,320,438,458,495] Actuated Objects [116, 117, 127, 159, 167, 243-245, 258, 431, 443, 472, 473] Combinations [29,52,53,66,98,101,117,136,169,177,209,225,327] Other Types [31,65,86,136,206,239,304,337,338,443,476] 1 : 1 [25,30,33,54,67,76,103,118,133,153,216,226,228,251,252,310,313,329,358,361,450,481,482,494] 1 : m [131,142,145,163,176,177,212,235,246,328,416,425] n : 1 [31,112,159,275,317,338,345,364,369,382,430] n : m [200,221,328,408,415,431] Small [86,179,258,328,374,425,443] [ 11,14,18,19,49,55,116,117,127,130,136,163,167,193,221,242,244,245,257,335,340,407,408,429,445,451] [ 29,158,162,191,210,220,229,230,262,272,285,289,315,337,342,346,350,370,372,406,429,464,467] Large [2,7,320,458,475] Near Far ...
... Their results show that there is a significant increase in several areas of the brain when people view fake websites vs. real websites even though users' accuracy in identifying the legitimacy of the site was close to 50%. The study of [32] investigated users' processing of real vs. fake voices in the context of voice impersonation attacks, with similar findings as to the above studies. ...
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... Per Hirshfield et al. [2], the tradeoffs between language and visual gesture may be highly sensitive to teammates' level and type of cognitive load. It may not be advantageous to rely on visual communication in contexts with high visual load, or to rely on linguistic communication in contexts with high auditory or working memory load. ...
... This latter example presents a sliding scale with respect to the primary purpose of each cursor movement. In a process later also described by Hincks et al. (2017), the This is the Accepted Manuscript version of an article accepted for publication in Journal of Neural Engineering. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. ...
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... For this purpose, a comprehensible alternative was conceived in the usage of the Badgematic Flexi Type 900 (59 mm) press as a shared task to produce pin-back buttons (Badgematic, 2020). The use of stand-ins for real manufacturing tasks can be found in several research setups involving HRC Williams et al., 2020). ...
... Recently, deep learning approaches including feed-forward networks, convolution neural networks (CNNs), and recurrent neural networks (RNNs) have shown good performance in many fields. RNNs perform especially well when applied to sequential problems such as video description [1], [2], speech recognition [3], [4], neural machine translation [5]- [7], sentiment classification from text [8], and detection from multidimensional data [9]. A RNN is a recurrent network which uses the hidden state of the previous time step as input for the current time step t as follows: ...
... Robotic Arms [21,25,27,33,51,59,79,105,133,136,140,153,182,262,270,282,285,325,326,341,354,358,372] Drones [15,58,76,96,114,171,261,332,382,436,450,451,475,482,494] Mobile Robots [53,91,112,163,169,177,191,197,209,210,212,221,263,305,328,346,370,407,418,445,467,468] Humanoid Robots [14,29,59,158,183,254,262,372,429,439,440] Vehicles [2,7,223,300,314,320,438,458,495] Actuated Objects [116, 117, 127, 159, 167, 243-245, 258, 431, 443, 472, 473] Combinations [29,52,53,66,98,101,117,136,169,177,209,225,327] Other Types [31,65,86,136,206,239,304,337,338,443,476] 1 : 1 [25,30,33,54,67,76,103,118,133,153,216,226,228,251,252,310,313,329,358,361,450,481,482,494] 1 : m [131,142,145,163,176,177,212,235,246,328,416,425] n : 1 [31,112,159,275,317,338,345,364,369,382,430] n : m [200,221,328,408,415,431] Small [86,179,258,328,374,425,443] [ 11,14,18,19,49,55,116,117,127,130,136,163,167,193,221,242,244,245,257,335,340,407,408,429,445,451] [ 29,158,162,191,210,220,229,230,262,272,285,289,315,337,342,346,350,370,372,406,429,464,467] Large [2,7,320,458,475] Near Far ...
