Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 1998. / Includes bibliographical references (leaves 134-143). / by Thomas Michael Talavage. / Ph.D.

Thesis (Ph. D. in Electrical and Medical Engineering)--Harvard-MIT Division of Health Sciences and Technology, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 121-128). / Magnetoencephalography (MEG) non-invasively offers information about neural activity in the brain by measuring its magnetic field. Estimating the cerebral sources of neural activity from MEG is an ill-posed inverse problem that presents several challenges. First, this inverse problem is high-dimensional, as the number of possible sources exceeds the number of MEG recording sensors by at least an order of magnitude. Second, even though the neural activity has a strong temporal dynamic and the MEG recordings are made at high-temporal resolution, the temporal dynamic is usually not exploited to enhance the spatial accuracy of the source localization. Third, whereas a dynamic form of the MEG source localization problem can be easily formulated as a state-space model (SSM) problem, the high dimension of the resulting state-space makes this approach computationally impractical. In this thesis we use a SSM to characterize from MEG recordings the spatiotemporal dynamics of underlying neural activity. We use the Kalman fixed-interval smoother (KS) to obtain maximum a posteriori (MAP) estimates of the hidden states, the expectation-maximization (EM) algorithm to obtain maximum-likelihood (ML) estimates of the parameters defining the SSM, and standard model-selection criteria to choose among competing SSMs. Because of the high dimensionality of the SSM, the computational requirements of these algorithms are high, and preclude the use of current frameworks for MEG analysis. We address these computational problems by developing an accelerated, distributed-memory version of the KS+EM algorithm appropriate for the analysis of high-dimensional data sets. Using the accelerated KS+EM algorithm, we introduce two SSM-based algorithms for MEG data analysis: KronEM (Kronecker Product modeling using KS+EM) and StimEM (Stimulus effect estimation using KS+EM). KronEM characterizes the spatiotemporal covariance of MEG recordings using an parameterization that efficiently describes the rhythmicity present in resting state neural activity. KronEM describes the data as a sum of components composed of a time-invariant spatial signature and a temporal second-order autorregresive process. In comparison with previous attempts at modeling resting-state activity, the KronEM algorithm estimates the number of such components using the data, and is able to identify an arbitrary number of them. We illustrate these properties on a simulation study, and then analyze MEG recordings collected from a human subject in resting state. The KronEM algorithm recovered components consistent with well-known physiological rhythmic activity. We then compare the resulting topographic maps of frequency with multi-taper based ones, and show that KronEM-based maps better localize naturally occurring rhythms. These results make the KronEM algorithm a useful single-trial frequency analysis technique. StimEM estimates neural activity using MEG recordings made in evoked-potential studies, in which the subject is repeatedly presented with a stimulus and only the stimulus effect is of interest. In contrast with other dynamic source-localization techniques, StimEM accepts arbitrary description of neural dynamics, parameterized as a weighted sum of user-defined candidates, and finds the MAP estimate of the weights. Using the estimated dynamics, StimEM generates a time-resolved ML estimate of the evoked-potential activity in the cortex. We illustrate the ability of StimEM to identify dynamics in a simulated data set of realistic dimensions, and show that the estimates improve substantially when dynamics are taken into account. We next analyze experimental MEG data from an auditory evoked-potential study and show that StimEM identifies dynamics consistent with neurophysiology and neuroanatomy and improves the localization of the evoked cortical response. In summary, we establish the feasibility of non-approximate SSM-based analysis of high-dimensional state-space models using a distributed-memory implementation of an accelerated KS+EM algorithm. We develop two novel algorithms to analyze MEG data in resting-state and evoked potential studies, and show that SSM analysis improves substantially on previous non-SSM based techniques. / by Antonio Molins Jiménez. / Ph.D.in Electrical and Medical Engineering

No description available.

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: Ph. D. in Medical Engineering and Medical Physics, Harvard-MIT Program in Health Sciences and Technology, 2020 / Cataloged from student-submitted PDF of thesis. / Includes bibliographical references (pages 208-242). / Contemporary technological approaches to address limb loss and neuromuscular dysfunction consist of synthetic, mechanical devices which lack an intimate bidirectional interface with nervous tissues. On the therapeutic front, the current amputation paradigm disrupts neuromuscular architecture, discards sensory organs and provides no anatomical or prosthetic replacement. This precludes the generation of afferent sensory feedback, which is critical for sensory integration, motor planning, peripheral and central neurological health, and myoelectric prosthesis control. Utilizing a paradigm of coevolution, I simultaneously engineer neuromuscular anatomy and bioelectronics to enable seamless, bidirectional neuroprosthetic interfacing. In this dissertation, I describe the design and preclinical validation of the regenerative agonist-antagonist myoneural interface (AMI) and myodermal interface (MI), which are reconstructive surgical models to restore musculotendinous and cutaneous sensory feedback, respectively. Then, through case-control studies, the functional outcomes of human subjects who have undergone below-knee and above-knee amputations incorporating native AMIs are compared to standard amputation controls. The effect of AMI amputation on sensorimotor neuroplasticity is investigated through anatomical and functional neuroimaging. These preclinical and clinical evaluations demonstrate the a) production of graded efferent and afferent signals, b) the maintenance of peripheral limb volume and central sensorimotor substrates, c) improvements in phantom sensation, phantom pain, and neuroprosthetic controllability, and d) decreased dependence on compensatory visuomotor circuitry. To address challenges with functional electrical stimulation (FES) of neuromusculature, employed for prosthetic feedback and control, I develop a closed-loop functional optogenetic stimulation system (FOS) for peripheral neuromuscular control. This system demonstrates greater accuracy, biomimetic orderly recruitment of fibers, and minimized fatigue during cyclic movements as compared to FES. Spanning from animal models to human implementation, this dissertation presents 1) a model to design new surgical techniques for afferent/efferent signaling, 2) characterize the physiology following clinical translation, and 3) recursively apply the lessons to the design of neural interfaces back at the bench. In summary, the results of this work steer a shift of the clinical amputation paradigm towards one that performs strategic rewiring of neuromuscular constructs to enable improved neurological health and neural interfacing. / Shriya Srinivasan. / Ph. D. in Medical Engineering and Medical Physics / Ph. D. in Medical Engineering and Medical Physics Harvard-MIT Program in Health Sciences and Technology

Thesis: Ph. D. in Medical Engineering and Medical Physics, Harvard-MIT Program in Health Sciences and Technology, 2018 / Cataloged from PDF version of thesis. Cataloged from PDF of thesis. / Includes bibliographical references (pages 379-400). / For persons living with lower extremity amputation, the prosthetic socket -- the cup-like interface connecting the residuum to prosthesis - is considered the most critical component. It must be custom-made and tailored to each individual user, and if not fit properly can significantly hinder quality of life. As an alternative to conventional fabrication practices that involve subjective input from a clinician, computational modeling-based socket design practices have emerged. Despite early success, its clinical implementation and potential for broad accessibility are limited since it relies on expensive imaging technologies and robotic indentation devices. Medical ultrasound imaging, a cost-effective modality that can be used at the bedside, is a promising and clinically-viable solution. In order for ultrasound to become a viable scanning method for this application, technological development was necessary that allows for three-dimensional acquisition of (1) limb geometry and (2) mechanical tissue properties. Toward this goal, we first present the design of a novel multi-modal imaging system for rapidly acquiring volumetric ultrasound imagery of human limbs. Second, we present results of two studies that evaluate the use of ultrasound indentation and shear wave elastography (SWE) to characterize tissue biomechanics: the former to investigate how SWE is affected by transducer force, and the latter presenting a novel approach for constitutive parameter identification using a combination of finite element analysis (FEA), indentation, and SWE. Finally, we demonstrate that SWE may be performed using a non-contact approach, allowing for human limb data to be collected under discrete transducer-independent loading conditions. The techniques and results presented in this thesis highlight the potential for ultrasound imaging for improved prosthesis design, as well as more broadly to quantitative musculoskeletal tissue assessment for a variety of clinical applications. Specifically, data may be directly incorporated into computational prosthetic socket design practices that are in development in the Biomechatronics Group. / Bryan James Ranger. / Ph. D. in Medical Engineering and Medical Physics / Ph. D. in Medical Engineering and Medical Physics Harvard-MIT Program in Health Sciences and Technology

Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, February 2019 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 71-81). / Originally viewed as 'garbage bags' which cells release to dispose of unwanted material, extracellular vesicles (EVs) have emerged as potent messengers that package and disseminate biochemical signals. This newly recognized mode of communication between cells has brought unprecedented therapeutic opportunities; at least 8 clinical trials and 7 companies are investigating or developing EVs as therapeutic products. As the EV industry rapidly grows, there is a rising demand for strategies that facilitate EV manufacturing. In this thesis, we address several challenges in EV manufacturing. By quantifying how many EVs a cell can release before it divides, we discovered that EV output increases as cells divide more slowly, providing a new way to maximize EV output from cells. Using our mathematical description of EV output, we built a computational model to estimate costs of EV manufacturing. Selecting cells with higher EV output despite slower proliferation can drastically lower costs. Meanwhile, although ultracentrifugation is the current standard for purifying EVs, we found that ultrafiltration-specifically tangential-flow filtration-is a more economical and scalable alternative, and we experimentally determined its utility for scaling up EV purification. For quality control, we established a suite of potency assays to measure the overall inflammatory action of EVs derived from human stem cells. Significant variability in EV potency between cells of different donors was detected, substantiating the need to robustly screen for appropriate cell sources when manufacturing EVs. Towards controlling EV function, we genetically constructed a versatile, multi-domain ligand that localizes to and modifies the surface of vesicles. Integrating biological, processing, and economic aspects of EV manufacturing, this thesis recommends strategies that may accelerate commercialization and clinical translation of EV therapy. / by Kelvin S. Ng. / Ph. D. / Ph.D. Harvard-MIT Program in Health Sciences and Technology

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2005. / Includes bibliographical references (leaves 56-57). / Executive Summary: In this thesis, I examine faculty inventors' involvement in university spin-off firms formed to commercialize their inventions. In particular, I analyze the association between a faculty inventor's various roles in commercializing his/her invention and the performance of the ensuing fledging ventures. The study is based on a group of spin-off firms from MIT in the biomedical/life science sector between 1976 and 2003. Structured questionnaires were distributed to the 110 faculty inventors identified by the technology licensing office (TLO) in April 2005, yielding 31 valid responses covering 60 companies. / by Hong Hocking Cheng. / S.M.

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2006. / Includes bibliographical references (leaves 57-59). / I study several aspects of the value in performing oncology clinical trials using screening biomarkers to preferentially select and enroll responders. From trial reports and investigational reports on potential biomarkers, I construct a series of six cases comparing the trial as conducted to a hypothetical trial using different screening and eligibility criteria. These cases illustrate, within limits of the model, what difference the use of a plausible biomarker test may have on trial size, cost, number of patients screened, and number of patients exposed to experimental treatment without benefit. / by David Wine. / S.M.

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 2006. / Includes bibliographical references (p. 79-82). / The use of stents following angioplasty in ischemic arterial beds is limited by complications and continuing vascular deterioration. A phenomenon called stent restenosis post procedure exists which puts patients at a relatively high risk for vessel stenosis and occlusion. Stent restenosis may eventually lead to clinical symptoms such as myocardial infarction, stroke or limb loss, and if overlooked might lead to death. Within five years of stenting, a significant portion of patients require additional surgical intervention. A novel stent-based, implantable, and wireless approach for real-time monitoring of vessel patency at the site of coronary stents is proposed, will provide a measure of efficacy of stenting and of the pharmacologic regiment to mitigate the risk of vessel stenosis and narrowing due to the underlying. The purpose of this thesis is to explore and test the Hypotheses that there is a market for a direct, non-invasive monitoring of vessel patency at the site of a coronary stent; and that an implantable, wireless, stent-based device to monitor blood flow rate through a coronary stent can be designed and built. / (cont.) A literature survey of late clinical studies and the opinion of numerous specialist clinicians collected in interviews and preliminary questionnaire, demonstrate sufficient clinical ambiguity regarding the safety of coronary stents, including Drug-Eluting Stents (DES) portrait an underserved clinical need to justify the introduction of a direct, non-invasive modality for post-op monitoring of vessel patency at the site of a coronary stent. / by Baruch Schori. / M.B.A. / S.M.

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2008. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 43-45). / Large pharmaceutical companies (Multinational Pharmaceutical Companies or MPCs) have struggled in recent years with the rapidly accelerating costs of drug-discovery research and development. These costs continue to rise while resulting in fewer drug leads. Several industries have realized significant cost savings by outsourcing operations to countries with low-cost labor like India and China. Several factors have traditionally kept MPCs from moving high value, patent-sensitive discovery operations to India despite these drastically lower labor costs. However recent improvements in the Indian patent system in response to WTO compliance have stimulated an increase in both domestic investment in innovative research and in deal making within the life science industry. Nonetheless, there are few systematic analyses of the quantity of deal making between international and domestic Indian firms. Based on our analysis, we conclude that MPCs are establishing alliances at a greater rate than Biotechnology-based firms. In addition, we find that the improvements in patent law have created the structures necessary to stimulate innovation-based life science companies to establish relationships with Indian firms that put their most important types of intellectual property at risk. / by Patrick Brian McGarvey. / S.M.