Hendrik van der Loos

Associate Professor

Relevant Degree Programs


Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.


Having Dr. Van der Loos as my supervisor has made my journey at UBC an invaluable and pleasant experience. In addition to being an unwavering support, he is very patient, receptive and always encourages me to reach new heights in my academic pursuits. I have learned so much under his mentorship and I could not be more grateful to have him as my supervisor.

Anonymous (2017)


Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - Nov 2020)
Negotiating with robots: meshing plans and resolving conflicts in human-robot collaboration (2017)

For both humans and robots, one of the key elements of collaboration is the collaborating agents’ability to communicate and mesh their individual plans with each other. Even after the collaborators have decided on a joint task, the details of the task such as the how, when, and where are often determined as the collaborative activity unfolds. The primary objective of this thesis is to enable fluent communication between human and robotic agents such that they can interactively figure out unspoken details and resolve unforeseen conflicts that arise during a human-robot collaboration.The author first explores whether robot nonverbal cues inspired by human behaviours can elicitdesirable responses from a human user to interweave unspoken – yet essential – spatial-temporal details of an interaction. Results from a series of experiments demonstrate that a robot cue, like gaze, can have a significant influence on when a human recipient reaches out to receive an object from a robot. Subsequently, the author focuses on hesitation gestures – a type of gesture humans naturally useto express uncertainty – to explore whether members of a human-robot dyad can negotiate a desired outcome of an interaction through a nonverbal dialog. The author presents a reactive, real-time trajectory generator, the Negotiative Hesitation Generator (NHG), which has been devised to enable such nonverbal negotiation to take place between a human and a robot. The NHG was implemented on a robot for human-robot interaction experiments where, by design, spontaneous resource conflicts often arose between the two agents. Results from these studies suggest that use of the NHG can enable a type of nonverbal negotiation of resource conflicts to take place. They also demonstrate how such real-time negotiations between a human-robot dyad can lead to a faster resolution of conflicts and a significantly improved outcome of the collaborative task, without jeopardizing the safety of the user. This thesis advances our understanding of the influence that nonverbal robot behaviours can have on human users. It also demonstrates the feasibility and efficacy of nonverbal negotiations as a mode of interaction for human-robot collaboration.

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Reducing compensatory movements in stroke therapy through the use of robotic devices and augmented feedback (2017)

Compensatory movements are commonly employed by stroke survivors to adapt to the loss of motor function. However, their long-term use can be detrimental to post-stroke recovery of function. In this work, we focused on trunk displacement, which is a compensatory movement that stroke survivors use when reaching forward. Current therapeutic practices to reduce this tendency rely on the use of physical restraints to secure a person to a chair. An alternate approach to reduce compensation is the use of active technology that delivers augmented feedback about trunk movement. Using this methodology provides several advantages over physical restraints, such as: the person is actively involved in the planning and executing of the movement rather than relying on a physical barrier that continuously prevents trunk movement; the feedback intensity, frequency, and thresholds can easily be modified in real time; the system is less intrusive as it does not require the person to be strapped or secured to a chair by someone else; it can be used safely without direct supervision; the trunk compensation feedback can be used as a variable inside a motivating video game scenario.This dissertation is comprised of three studies to investigate: the extent of stroke survivors’ trunk displacement when reaching forward to targets at different heights (Study 1), the use of visual and force feedback (Study 2), and the importance of including game scores (Study 3) to reduce trunk compensation. The results from these studies suggest that target height influences the degree of trunk compensation of hemiparetic participants. In addition, the use of visual and force feedback to cue participants about their level of trunk compensation can lead to a reduction of this movement. Similarly, the use of game scores resulted in a reduction of trunk compensation. No feedback modality or combination was superior to another for reducing trunk displacement.The findings from this work suggest that the use of augmented feedback is a viable approach to reduce trunk compensation in hemiparetic stroke survivors. These ideas should be tested in long-term interventions before we can make a final recommendation to the rehabilitation community. Supplementary/video material is available at: http://hdl.handle.net/2429/62493

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Upper-body motion coordination after stroke: Insights from kinematic and muscle synergies (2017)

Several studies suggest that the human central nervous system controls groups of muscles and/or joints (synergies) rather than controlling each muscle or joint separately to reduce the dimensionality of motor planning and execution. Furthermore, recent studies with stroke survivors indicate that motor impairment after stroke is due to a disruption in the recruitment and the combination of the motor synergies. The objective of the work in this thesis was to investigate human upper body motor coordination and to demonstrate the viability of synergistic motor control theory in describing the natural upper body movements, as well as quantifying the effects of stroke on motion generation. A critique of previous studies on this topic is that the synergies they report are task-specific and reflect the biomechanical constraints of the task rather than the neural strategies of motor control. To address this, the studies covered in this dissertation were focused on quantification of motor synergies demonstrated during exploratory motor tasks. Exploratory motions have the potential to reveal individualized motion tendencies or motor deficits.The first study compared the robustness of matrix factorization methods reported in literature to characterize motor synergies, and showed that non-negative matrix factorization is more suited for synergy analysis. The second study established how much exploratory motion data is needed to reliably extract motor synergies of healthy and stroke survivor individuals. A group of healthy adults were recruited for the third study. The results showed that motor synergies between the dominant and non-dominant hands of healthy adults are similar (within-subject similarities) and that healthy adults share a set of “healthy” motor synergies (between-subjects similarities). The fourth study explored how stroke changes motor synergies. The study showed that healthy motor synergies are preserved in the less-affected arm of stroke survivors. However, the motor synergies of the stroke-affected arm are altered through merging and fractionation of healthy synergies and these processes are a function of the individual’s impairment and time post-stroke. These results offer a better understanding of motor synergies and can improve rehabilitation practices by identifying strengthening physical therapy exercises that utilize or promote the use of “healthy” synergies.

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Master's Student Supervision (2010 - 2018)
Participatory design methods for medical device innovation in Uganda (2018)

Orthopaedic injury is set to become the 3rd leading cause globally of disability and death by 2030. Despite the cost-effectiveness and efficacy of orthopaedic surgery, there is a significant gap in access to care. Of importance to delivering safe, modern, and timely treatment is access to high quality medical devices. This access however is limited by a mismatch between the technology that industry is developing and what is needed in low- and middle-income country (LMIC) contexts. Through field study in a Ugandan hospital setting, this research examined two methods for participatory design of medical devices in LMICs that seek to overcome gaps in understanding between designers and users across different cultural and professional backgrounds, as well as the "Expert User" problem. The use of Cultural Probes and Outcome-Driven Innovation has proven useful to perform detailed needs finding, filtering and prioritization, which are critical early steps of the design process. The results point to a myriad of challenges across domains: technology, systemic, infrastructure, staff, and patients, which all contribute to difficulty in providing timely, safe surgical care. They also give designers insight into which technology areas are the most underserved, and which attributes of technology might warrant special consideration in the design process. From these results, the design of a bone reduction and alignment device was prototyped, with feedback sought from Ugandan surgeons. The many lessons from this research have been applied in the past five years to the development and commercialization of the DrillCover product through Arbutus Medical. It is our hope that industry, engineers, and designers take the lead in addressing the medical device mismatch by leveraging these participatory design methods when embarking on medical device innovation projects for LMIC users, and importantly, include these users in a collaborative design process for a higher likelihood of success.

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Developing Control Strategies to Mitigate Injury after Falling Backward with a Lower Limb Exoskeleton (2017)

Powered lower limb exoskeletons (LLEs) are wearable robotic aids that provide mobility assistance for people with mobility impairments. Despite their advanced design, LLEs are still far from being effective assistive devices that can be used to perform activities of daily living. The main challenge in the operation of a LLE is to ensure that balance is maintained. However, maintaining an upright stance is not always achievable and regardless of the quality of user skill and training, inevitably falls will occur. Currently, there is no control strategy developed or implemented in LLEs that help reduce the user’s risk of injury in the case of an unexpected fall. In this thesis, an optimization methodology was developed and used to create a safer strategy for exoskeletons falling backwards in a simulation environment. Due to the data available regarding the biomechanics of human falls, the optimization methodology was first developed to study falls with simulation parameters characteristic of healthy people. The resulting optimal fall strategy in this study had similar kinematic and dynamic characteristics to the findings of previous studies on human falls. Rapid knee flexion at the onset of the fall, and knee extension prior to ground contact are examples of these characteristics. Following this, the optimization methodology was extended to include the characteristics of an exoskeleton. The results revealed that the hip impact velocity was reduced by 58% when the optimal fall strategy was employed compared to the case where the exoskeleton fell with locked joints. It was also shown that in both cases of optimal human and human-exoskeleton falls, the models contacted the ground with an upright trunk with a near-zero trunk angular velocity to avoid head impact. These results achieved the thesis goal of developing an effective safe fall control strategy. This strategy was then implemented in a prototype exoskeleton test device. The experimental results validated the simulation outcomes and support the feasibility of implementing this control strategy. Future studies are needed to further examine the effectiveness of applying this strategy in an actual LLE.

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Two-handed coordination in robots: by combining two one-handed trajectories based on probabilistic models of taskspace effects (2017)

Human environments and tools are commonly designed to be used by two-handed agents. In order for a robot to make use of human tools or to navigate in a human environment it must be able to use two arms. Planning motion for two arms is a difficult task as it requires taking into account a large number of joints and links and involves both temporal and spatial coordination. The work in this thesis addresses these problems by providing a framework to combine two single-arm trajectories to perform a two-armed task. Inspired by results indicating that humans perform better on motor tasks when focusing on the outcome of their movements rather than their joint motions, I propose a solution that considers each trajectory's effect on the taskspace. I develop a novel framework for modifying and combining one-armed trajectories to complete two-armed tasks. The framework is designed to be as general as possible and is agnostic to how the one-armed trajectories were generated and the robot(s) being used. Physical roll-outs of the individual arm trajectories are used to create probabilistic models of their performance in taskspace using Gaussian Mixture Models. This approach allows for error compensation. Trajectories are combined in taskspace in order to achieve the highest probability of success and task performance quality. The framework was tested using two Barrett WAM robots performing the difficult, two-armed task of serving a ping-pong ball. For this demonstration, the trajectories were created using quintic interpolations of joint coordinates. The trajectory combinations are tested for collisions in the robot simulation tool, Gazebo. I demonstrated that the system can successfully choose and execute the highest-probability trajectory combination that is collision-free to achieve a given taskspace goal. The framework achieved timing of the two single-arm trajectories optimal to within 0.0389 seconds -- approximately equal to the time between frames of the 30 Hz camera. The implemented algorithm successfully ranked the likelihood of success for four out of five serving motions. Finally, the framework's ability to perform a higher-level tasks was demonstrated by performing a legal ping-pong serve. These results were achieved despite significant noise in the data.

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Use of activity theory as basis for a novel needs-finding technique for medical device development in low-resource environments (2017)

According to the World Health Organization, appropriate medical devices are not sufficiently available in low-resource environments within low and middle income countries. Lack of systematic structures, challenges with entering existing markets and incomplete understanding of design needs within these contexts are the key reasons for this problem. It is challenging to understand the needs for medical device development in low and middle income countries because the problem space has complex socioeconomic, political, technical and clinical constraints to navigate. Existing needs-finding techniques for engineering design do not provide an explicit means of identifying and synthesizing these complex factors. The main contribution of this thesis is development of a novel needs-finding technique for medical device development, specifically for low-resource environments. The proposed novel technique is empirically compared to the needs-finding technique of the well-established Stanford Biodesign Process. In a series of studies, the Activity Theory-based Needs-finding Technique (ATNF), based on Activity Theory, was integrated into the engineering design process. The cultural historical Activity Theory, rooted in Russian psychology, provides a framework for analyzing human activity and social structures. The ATNF proposes a modified activity system that explicitly situates technology within an activity. Mapping activities and identifying tension points within them allow for a fuller understanding of design needs. The ATNF method was initially investigated through its detailed application on a case study in the field of health technology development in low-resource environments. Thereafter, an ethnographic comparative study was completed to investigate the ATNF technique and the Biodesign technique by examining the differences between the needs statements and the process of developing them. The results indicate that the novel ATNF method is more effective in identifying an appropriate scope and desired change. However, the design artefacts from the ATNF and the Biodesign techniques equally cover socioeconomic, clinical and technical issues. This suggests that the strength of the ATNF technique is in creating connections between issues to develop an appropriate scope and in identifying desired change. The research supports that the ATNF technique is a viable needs-finding method and that it has particular strengths that could be leveraged for medical device development in low-resource environments.

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Design and Evaluation of Trajectory-Based Tasks in a Thin-Seam Perspective-Corrected Cubic Display (2016)

This thesis describes the design and evaluation of wire-tracing task in pCubee, an improved version of hand-held perspective-corrected display that allows the user to observe and interact with 3D content visualized inside the cubic system. In order to overcome visual discontinuity issues identified from previous works, we redesigned pCubee system using OLED panels and FPGA-based display controller to achieve reduced seam size and compact form-factor. We investigated user performance with the new system using a trajectory-based wire-tracing task where users were asked to move a ring along wires. Experiments were conducted to evaluate the impact of ring radius, wire length and curvature. Analysis of results revealed that a linear model similar to the steering law for 2D tunnel task applies to 3D trajectory-based task in pCubee as well, exhibiting an increase of task completion time when smaller ring or longer wire is used. Our study complemented the theory that 3D interaction in virtual reality system follows existing principle for 2D tasks, and also identified a potential method to evaluate interaction designs for geometric displays. This work could help motivate future development of pCubee and guide interaction design for similar systems.

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The evolution from Rydberg gas to plasma in an atomic beam of Xe : with comparative simulations to a strongly blockaded Rydberg gas of Rb (2015)

We study a supersonic beam of cold, dense, xenon Rydberg atoms as it evolves to an ultracoldplasma. At early times, while the free electron density is low, d-series Rydbergs atoms undergolong-range ℓ-mixing collisions producing states of high orbital angular momentum. These high-ℓstates drive dipole-dipole interactions where Penning ionization provides a seed of electrons in a cloud of Rydberg atoms excited into the 51d state. The electron density increases and reachesthe threshold for avalanche into plasma at 25 μs. After 90 μs the plasma becomes fully formeddeveloping rigidity to a 432 V/cm ionizing field as well as sensitivity to a weak 500 mV/cm field.A shell model was developed to understand the dynamics behind this process.In addition, in collaboration with the Weidemüller group, a model was developed using Penningionization to seed the spontaneous avalanche of a cloud of strongly blockaded Rydberg atoms in a MOT.

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