About

Tim Kiemel is an Associate Research Professor in the Department of Kinesiology at the University of Maryland's School of Public Health. His research focuses on the neural control of movement, specifically studying behaviors such as walking and the postural control of standing in humans, as well as swimming in lampreys. His work emphasizes the development of system-level models that illuminate key aspects of neural control, utilizing empirical data to develop and test these models.

Research topics

• Computer Science
• Artificial Intelligence
• Psychology
• Physics
• Neuroscience
• Medicine
• Physical medicine and rehabilitation
• Classical mechanics
• Mathematics
• Cognitive psychology
• Engineering

Selected publications

• Modeling Human-Human Collaboration: A Connection Between Inter-Personal Motor Synergy and Consensus Algorithms

  2022 American Control Conference (ACC) · 2022-06-08

  article

  Many day-to-day activities involve people working collaboratively toward reaching a desired outcome. Previous research in motor control and neuroscience have proposed inter-personal motor synergy (IPMS) as a mechanism of collaboration between people, referring to the idea of how two or more people may work together "as if they were one" to coordinate their motion. In motor control literature, the uncontrolled manifold (UCM) is used for quantifying IPMS. According to this approach, coordinated motion is achieved by stabilizing of a performance variable (e.g., an output in a collaborative output tracking task). We show that the UCM approach is closely related to the well-studied consensus approach in multi-agent systems that concerns processes by which a set of interacting agents agree on a shared objective. To explore the connection between these two approaches, in this paper, we provide a control-theoretic model that represents the systems-level behaviors in a collaborative task. In particular, we utilize the consensus protocol and show how the model can be systematically tuned to reproduce the behavior exhibited by human-human collaboration (HHC) experiments. We discuss the association between the proposed control law and the UCM approach and validate our model using experimental results previously collected from an inter-personal finger force production task.

  PublisherDOI

• Modeling Human-Human Collaboration: A Connection Between Inter-Personal Motor Synergy and Consensus Algorithms

  arXiv (Cornell University) · 2021-10-20

  preprintOpen access

  Many day-to-day activities involve people working collaboratively toward reaching a desired outcome. Previous research in motor control and neuroscience have proposed inter-personal motor synergy (IPMS) as a mechanism of collaboration between people, referring to the idea of how two or more people may work together "as if they were one" to coordinate their motion. In motor control literature, uncontrolled manifold (UCM) is used for quantifying IPMS. According to this approach, coordinated motion is achieved through stabilization of a performance variable (e.g., an output in a collaborative output tracking task). We show that the UCM approach is closely related to the well-studied consensus approach in multi-agent systems that concerns processes by which a set of interacting agents agree on a shared objective. To explore the connection between these two approaches, in this paper, we provide a control-theoretic model that represents the systems-level behaviors in a collaborative task. In particular, we utilize the consensus protocol and show how the model can be systematically tuned to reproduce the behavior exhibited by human-human collaboration experiments. We discuss the association between the proposed control law and the UCM approach and validate our model using experimental results previously collected from an inter-personal finger force production task.

  PublisherOA PDFDOI

• Unveiling the neuromechanical mechanisms underlying the synergistic interactions in human sensorimotor system

  Scientific Reports · 2021 · 5 citations

  • Computer Science
  • Computer Science
  • Neuroscience

  Motor synergies are neural organizations of a set of redundant motor effectors that interact with one another to compensate for each other's error and ensure the stabilization of a performance variable. Recent studies have demonstrated that central nervous system synergistically coordinates its numerous motor effectors through Bayesian multi-sensory integration. Deficiency in sensory synergy weakens the synergistic interaction between the motor effectors. Here, we scrutinize the neuromechanical mechanism underlying this phenomenon through spectral analysis and modeling. We validate our model-generated results using experimental data reported in the literature collected from participants performing a finger force production task with and without tactile feedback (manipulated through injection of anesthetic in fingers). Spectral analysis reveals that the error compensation feature of synergies occurs only at low frequencies. Modeling suggests that the neurophysiological structures involving short-latency back-coupling loops similar to the well-known Renshaw cells explain the deterioration of synergy due to sensory deprivation.

  PublisherOA PDFDOI

• Interpersonal motor synergy: coworking strategy depends on task constraints

  Journal of Neurophysiology · 2021 · 2 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  To the best of our knowledge, this is the first study to investigate the coworking behavior or IPMS when an additional task constraint is imposed. Our proposed analytical framework quantifies IPMS and allows for investigating variability in offline (i.e., across multiple repetitions) and online (i.e., across time) control, which is novel in coworking research. Understanding variability while performing a task is essential, as repeating a task is not always possible, as in therapeutic contexts.

  PublisherDOI

• Multiple strategies to correct errors in foot placement and control speed in human walking

  Experimental Brain Research · 2020 · 16 citations

  Senior authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Physical medicine and rehabilitation
  PublisherDOI

• Body stiffness and damping depend sensitively on the timing of muscle activation in lampreys

  Integrative and Comparative Biology · 2018-05-29 · 51 citations

  articleOpen access

  Unlike most manmade machines, animals move through their world using flexible bodies and appendages, which bend due to internal muscle and body forces, and also due to forces from the environment. Fishes in particular must cope with fluid dynamic forces that not only resist their overall swimming movements but also may have unsteady flow patterns, vortices, and turbulence, many of which occur more rapidly than what the nervous system can process. Has natural selection led to mechanical properties of fish bodies and their component tissues that can respond very quickly to environmental perturbations? Here, we focus on the mechanical properties of isolated muscle tissue and of the entire intact body in the silver lamprey, Ichthyomyzon unicuspis. We developed two modified work loop protocols to determine the effect of small perturbations on the whole body and on isolated segments of muscle as a function of muscle activation and phase within the swimming cycle. First, we examined how the mechanical properties of the whole lamprey body change depending on the timing of muscle activity. Relative to passive muscle, muscle activation can modulate the effective stiffness by about two-fold and modulate the effective damping by >10-fold depending on the activation phase. Next, we performed a standard work loop test on small sections of axial musculature while adding low-amplitude sinusoidal perturbations at specific frequencies. We modeled the data using a new system identification technique based on time-periodic system analysis and harmonic transfer functions (HTFs) and used the resulting models to predict muscle function under novel conditions. We found that the effective stiffness and damping of muscle varies during the swimming cycle, and that the timing of activation can alter both the magnitude and timing of peak stiffness and damping. Moreover, the response of the isolated muscle was highly nonlinear and length dependent, but the body's response was much more linear. We applied the resulting HTFs from our experiments to explore the effect of pairs of antagonistic muscles. The results suggest that when muscles work against each other as antagonists, the combined system has weaker nonlinearities than either muscle segment alone. Together, these results begin to provide an integrative understanding of how activation timing can tune the mechanical response properties of muscles, enabling fish to swim effectively in their complex and unpredictable environment.

  PublisherOA PDFDOI

• A Tool to Quantify the Functional Impact of Oscillopsia

  Frontiers in Neurology · 2018-03-15 · 25 citations

  articleOpen access

  Background: Individuals with bilateral vestibular hypofunction (BVH) often report symptoms of oscillopsia during walking. Existing assessments of oscillopsia are limited to descriptions of severity and symptom frequency, neither of which provides a description of functional limitations attributed to oscillopsia. A novel questionnaire, the Oscillopsia Functional Impact scale (OFI) was developed to describe the impact of oscillopsia on daily life activities. Questions on the OFI ask how often individuals are able to execute specific activities considered to depend on gaze stability in an effort to link functional mobility impairments to oscillopsia for individuals with vestibular loss. Methods: Subjective reports of oscillopsia and balance confidence were recorded for 21 individuals with BVH and 48 healthy controls. Spearman correlation coefficients were calculated to determine the relationship between the OFI and oscillopsia visual analogue scale (OS VAS), oscillopsia severity questionnaire (OSQ), and Activities Specific Balance Confidence scale to demonstrate face validity. Chronbach’s α was calculated to determine internal validity for the items of the OFI. A one way MANOVA was conducted with planned post-hoc paired t-tests for group differences on all oscillopsia questionnaires using a corrected α = 0.0125. Results: The OFI was highly correlated with measures of oscillopsia severity (OS VAS; r = 0.69, p < 0.001) and frequency (OSQ; r = 0.84, p < 0.001) and also with the Activities Specific Balance Confidence scale (r = -0.84, p < 0.001). Chronbach’s α for the OFI was 0.97. Individuals with BVH scored worse on all measures of oscillopsia and balance confidence compared to healthy individuals (p’s < 0.001). Conclusions: The OFI appears to capture the construct of oscillopsia in the context of functional mobility. Combining with oscillopsia metrics that quantify severity and frequency allows for a more complete characterization of the impact of oscillopsia on an individual’s daily behavior. The OFI discriminated individuals with BVH from healthy individuals.

  PublisherOA PDFDOI

• Sensory-Challenge Balance Exercises Improve Multisensory Reweighting in Fall-Prone Older Adults

  Journal of Neurologic Physical Therapy · 2018-03-16 · 39 citations

  article

  BACKGROUND AND PURPOSE: Multisensory reweighting (MSR) deficits in older adults contribute to fall risk. Sensory-challenge balance exercises may have value for addressing the MSR deficits in fall-prone older adults. The purpose of this study was to examine the effect of sensory-challenge balance exercises on MSR and clinical balance measures in fall-prone older adults. METHODS: We used a quasi-experimental, repeated-measures, within-subjects design. Older adults with a history of falls underwent an 8-week baseline (control) period. This was followed by an 8-week intervention period that included 16 sensory-challenge balance exercise sessions performed with computerized balance training equipment. Measurements, taken twice before and once after intervention, included laboratory measures of MSR (center of mass gain and phase, position, and velocity variability) and clinical tests (Activities-specific Balance Confidence Scale, Berg Balance Scale, Sensory Organization Test, Limits of Stability test, and lower extremity strength and range of motion). RESULTS: Twenty adults 70 years of age and older with a history of falls completed all 16 sessions. Significant improvements were observed in laboratory-based MSR measures of touch gain (P = 0.006) and phase (P = 0.05), Berg Balance Scale (P = 0.002), Sensory Organization Test (P = 0.002), Limits of Stability Test (P = 0.001), and lower extremity strength scores (P = 0.005). Mean values of vision gain increased more than those for touch gain, but did not reach significance. DISCUSSION AND CONCLUSIONS: A balance exercise program specifically targeting multisensory integration mechanisms improved MSR, balance, and lower extremity strength in this mechanistic study. These valuable findings provide the scientific rationale for sensory-challenge balance exercise to improve perception of body position and motion in space and potential reduction in fall risk.

  PublisherDOI

• Intra-auditory integration between pitch and loudness in humans: Evidence of super-optimal integration at moderate uncertainty in auditory signals

  Scientific Reports · 2018-09-06 · 4 citations

  articleOpen access

  When a person plays a musical instrument, sound is produced and the integrated frequency and intensity produced are perceived aurally. The central nervous system (CNS) receives defective afferent signals from auditory systems and delivers imperfect efferent signals to the motor system due to the noise in both systems. However, it is still little known about auditory-motor interactions for successful performance. Here, we investigated auditory-motor interactions as multi-sensory input and multi-motor output system. Subjects performed a constant force production task using four fingers in three different auditory feedback conditions, where either the frequency (F), intensity (I), or both frequency and intensity (FI) of an auditory tone changed with sum of finger forces. Four levels of uncertainty (high, moderate-high, moderate-low, and low) were conditioned by manipulating the feedback gain of the produced force. We observed performance enhancement under the FI condition compared to either F or I alone at moderate-high uncertainty. Interestingly, the performance enhancement was greater than the prediction of the Bayesian model, suggesting super-optimality. We also observed deteriorated synergistic multi-finger interactions as the level of uncertainty increased, suggesting that the CNS responded to increased uncertainty by changing control strategy of multi-finger actions.

  PublisherOA PDFDOI

• List of Contributors

  Elsevier eBooks · 2017-01-01

  book-chapter
  PublisherDOI

Recent grants

• Collaborative Research: Understanding the Rules for Human Rhythmic Motor Coordination

  NSF · $394k · 2012–2016

Frequent coauthors

• John J. Jeka

  University of Delaware

  61 shared

• Avis H. Cohen

  14 shared

• Jae Kun Shim

  14 shared

• Kelvin S. Oie

  DEVCOM Army Research Laboratory

  8 shared

• Eric R. Anson

  University of Rochester

  7 shared

• Thelma L. Williams

  Princeton University

  7 shared

• Kyung Koh

  University of Maryland, Baltimore

  7 shared

• Peter Agada

  Temple University

  6 shared