Matching Items (324)
- All Subjects: Biomedical Engineering
- Resource Type: Text
Myoelectric control is lled with potential to signicantly change human-robot interaction.
Humans desire compliant robots to safely interact in dynamic environments
associated with daily activities. As surface electromyography non-invasively measures
limb motion intent and correlates with joint stiness during co-contractions,
it has been identied as a candidate for naturally controlling such robots. However,
state-of-the-art myoelectric interfaces have struggled to achieve both enhanced
functionality and long-term reliability. As demands in myoelectric interfaces trend
toward simultaneous and proportional control of compliant robots, robust processing
of multi-muscle coordinations, or synergies, plays a larger role in the success of the
control scheme. This dissertation presents a framework enhancing the utility of myoelectric
interfaces by exploiting motor skill learning and
exible muscle synergies for
reliable long-term simultaneous and proportional control of multifunctional compliant
robots. The interface is learned as a new motor skill specic to the controller,
providing long-term performance enhancements without requiring any retraining or
recalibration of the system. Moreover, the framework oers control of both motion
and stiness simultaneously for intuitive and compliant human-robot interaction. The
framework is validated through a series of experiments characterizing motor learning
properties and demonstrating control capabilities not seen previously in the literature.
The results validate the approach as a viable option to remove the trade-o
between functionality and reliability that have hindered state-of-the-art myoelectric
interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric
controlled applications beyond commonly perceived anthropomorphic and
\intuitive control" constraints and into more advanced robotic systems designed for
Parkinson's disease (PD) is a neurodegenerative disorder that produces a characteristic set of neuromotor deficits that sometimes includes reduced amplitude and velocity of movement. Several studies have shown that people with PD improved their motor performance when presented with external cues. Other work has demonstrated that high velocity and large amplitude exercises can increase the amplitude and velocity of movement in simple carryover tasks in the upper and lower extremities. Although the cause for these effects is not known, improvements due to cueing suggest that part of the neuromotor deficit in PD is in the integration of sensory feedback to produce motor commands. Previous studies have documented some somatosensory deficits, but only limited information is available regarding the nature and magnitude of sensorimotor deficits in the shoulder of people with PD. The goals of this research were to characterize the sensorimotor impairment in the shoulder joint of people with PD and to investigate the use of visual feedback and large amplitude/high velocity exercises to target PD-related motor deficits. Two systems were designed and developed to use visual feedback to assess the ability of participants to accurately adjust limb placement or limb movement velocity and to encourage improvements in performance of these tasks. Each system was tested on participants with PD, age-matched control subjects and young control subjects to characterize and compare limb placement and velocity control capabilities. Results demonstrated that participants with PD were less accurate at placing their limbs than age-matched or young control subjects, but that their performance improved over the course of the test session such that by the end, the participants with PD performed as well as controls. For the limb velocity feedback task, participants with PD and age-matched control subjects were less accurate than young control subjects, but at the end of the session, participants with PD and age-matched control subjects were as accurate as the young control subjects. This study demonstrates that people with PD were able to improve their movement patterns based on visual feedback of performance and suggests that this feedback paradigm may be useful in exercise programs for people with PD.
Detection of molecular interactions is critical for understanding many biological processes, for detecting disease biomarkers, and for screening drug candidates. Fluorescence-based approach can be problematic, especially when applied to the detection of small molecules. Various label-free techniques, such as surface plasmon resonance technique are sensitive to mass, making it extremely challenging to detect small molecules. In this thesis, novel detection methods for molecular interactions are described.
First, a simple detection paradigm based on reflectance interferometry is developed. This method is simple, low cost and can be easily applied for protein array detection.
Second, a label-free charge sensitive optical detection (CSOD) technique is developed for detecting of both large and small molecules. The technique is based on that most molecules relevant to biomedical research and applications are charged or partially charged. An optical fiber is dipped into the well of a microplate. It detects the surface charge of the fiber, which does not decrease with the size (mass) of the molecule, making it particularly attractive for studying small molecules.
Third, a method for mechanically amplification detection of molecular interactions (MADMI) is developed. It provides quantitative analysis of small molecules interaction with membrane proteins in intact cells. The interactions are monitored by detecting a mechanical deformation in the membrane induced by the molecular interactions. With this novel method small molecules and membrane proteins interaction in the intact cells can be detected. This new paradigm provides mechanical amplification of small interaction signals, allowing us to measure the binding kinetics of both large and small molecules with membrane proteins, and to analyze heterogeneous nature of the binding kinetics between different cells, and different regions of a single cell.
Last, by tracking the cell membrane edge deformation, binding caused downstream event – granule secretory has been measured. This method focuses on the plasma membrane change when granules fuse with the cell. The fusion of granules increases the plasma membrane area and thus the cell edge expands. The expansion is localized at the vesicle release location. Granule size was calculated based on measured edge expansion. The membrane deformation due to the granule release is real-time monitored by this method.
Comparison of feature selection methods for robust dexterous decoding of finger movements from the primary motor cortex of a non-human primate using support vector machine
Robust and stable decoding of neural signals is imperative for implementing a useful neuroprosthesis capable of carrying out dexterous tasks. A nonhuman primate (NHP) was trained to perform combined flexions of the thumb, index and middle fingers in addition to individual flexions and extensions of the same digits. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon action potential firing rates. The effect of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis, and Mutual Information Maximization was compared based on SVM classification performance. SVM classification was used to examine the functional parameters of (i) efficacy (ii) endurance to simulated failure and (iii) longevity of classification. The effect of using isolated-neuron and multi-unit firing rates was compared as the feature vector supplied to the SVM. The best classification performance was on post-implantation day 36, when using multi-unit firing rates the worst classification accuracy resulted from features selected with Wilcoxon signed-rank test (51.12 ± 0.65%) and the best classification accuracy resulted from Mutual Information Maximization (93.74 ± 0.32%). On this day when using single-unit firing rates, the classification accuracy from the Wilcoxon signed-rank test was 88.85 ± 0.61 % and Mutual Information Maximization was 95.60 ± 0.52% (degrees of freedom =10, level of chance =10%)
Noninvasive neuromodulation could help treat many neurological disorders, but existing techniques have low resolution and weak penetration. Ultrasound (US) shows promise for stimulation of smaller areas and subcortical structures. However, the mechanism and parameter design are not understood. US can stimulate tail and hindlimb movements in rats, but not forelimb, for unknown reasons. Potentially, US could also stimulate peripheral or enteric neurons for control of blood glucose.
To better understand the inconsistent effects across rat motor cortex, US modulation of electrically-evoked movements was tested. A stimulation array was implanted on the cortical surface and US (200 kHz, 30-60 W/cm2 peak) was applied while measuring changes in the evoked forelimb and hindlimb movements. Direct US stimulation of the hindlimb was also studied. To test peripheral effects, rat blood glucose levels were measured while applying US near the liver.
No short-term motor modulation was visible (95% confidence interval: -3.5% to +5.1% forelimb, -3.8% to +5.5% hindlimb). There was significant long-term (minutes-order) suppression (95% confidence interval: -3.7% to -10.8% forelimb, -3.8% to -11.9% hindlimb). This suppression may be due to the considerable heating (+1.8°C between US
on-US conditions); effects of heat and US were not separable in this experiment. US directly evoked hindlimb and scrotum movements in some sessions. This required a long interval, at least 3 seconds between US bursts. Movement could be evoked with much shorter pulses than used in literature (3 ms). The EMG latency (10 ms) was compatible with activation of corticospinal neurons. The glucose modulation test showed a strong increase in a few trials, but across all trials found no significant effect.
The single motor response and the long refractory period together suggest that only the beginning of the US burst had a stimulatory effect. This would explain the lack of short-term modulation, and suggests future work with shorter pulses could better explore the missing forelimb response. During the refractory period there was no change in the electrically-evoked response, which suggests the US stimulation mechanism is independent of normal brain activity. These results challenge the literature-standard protocols and provide new insights on the unknown mechanism.
Investigation of ultrasonically powered implantable microdevices for wireless tissue impedance measurements
Bioimpedance measurements have been long used for monitoring tissue ischemia and blood flow. This research employs implantable microelectronic devices to measure impedance chronically as a potential way to monitor the progress of peripheral vascular disease (PVD). Ultrasonically powered implantable microdevices previously developed for the purposes of neuroelectric vasodilation for therapeutic treatment of PVD were found to also allow a secondary function of tissue bioimpedance monitoring. Having no structural differences between devices used for neurostimulation and impedance measurements, there is a potential for double functionality and closed loop control of the neurostimulation performed by these types of microimplants. The proposed technique involves actuation of the implantable microdevices using a frequency-swept amplitude modulated continuous waveform ultrasound and remote monitoring of induced tissue current. The design has been investigated using simulations, ex vivo testing, and preliminary animal experiments. Obtained results have demonstrated the ability of ultrasonically powered neurostimulators to be sensitive to the impedance changes of tissue surrounding the device and wirelessly report impedance spectra. Present work suggests the potential feasibility of wireless tissue impedance measurements for PVD applications as a complement to neurostimulation.
Colorectal cancer is the second-highest cause of cancer-related deaths in the United States with approximately 50,000 estimated deaths in 2015. The advanced stages of colorectal cancer has a poor five-year survival rate of 10%, whereas the diagnosis in early stages of development has showed a more favorable five-year survival rate of 90%. Early diagnosis of colorectal cancer is achievable if colorectal polyps, a possible precursor to cancer, are detected and removed before developing into malignancy.
The preferred method for polyp detection and removal is optical colonoscopy. A colonoscopic procedure consists of two phases: (1) insertion phase during which a flexible endoscope (a flexible tube with a tiny video camera at the tip) is advanced via the anus and then gradually to the end of the colon--called the cecum, and (2) withdrawal phase during which the endoscope is gradually withdrawn while colonoscopists examine the colon wall to find and remove polyps. Colonoscopy is an effective procedure and has led to a significant decline in the incidence and mortality of colon cancer. However, despite many screening and therapeutic advantages, 1 out of every 4 polyps and 1 out of 13 colon cancers are missed during colonoscopy.
There are many factors that contribute to missed polyps and cancers including poor colon preparation, inadequate navigational skills, and fatigue. Poor colon preparation results in a substantial portion of colon covered with fecal content, hindering a careful examination of the colon. Inadequate navigational skills can prevent a colonoscopist from examining hard-to-reach regions of the colon that may contain a polyp. Fatigue can manifest itself in the performance of a colonoscopist by decreasing diligence and vigilance during procedures. Lack of vigilance may prevent a colonoscopist from detecting the polyps that briefly appear in the colonoscopy videos. Lack of diligence may result in hasty examination of the colon that is likely to miss polyps and lesions.
To reduce polyp and cancer miss rates, this research presents a quality assurance system with 3 components. The first component is an automatic polyp detection system that highlights the regions with suspected polyps in colonoscopy videos. The goal is to encourage more vigilance during procedures. The suggested polyp detection system consists of several novel modules: (1) a new patch descriptor that characterizes image appearance around boundaries more accurately and more efficiently than widely-used patch descriptors such HoG, LBP, and Daisy; (2) A 2-stage classification framework that is able to enhance low level image features prior to classification. Unlike the traditional way of image classification where a single patch undergoes the processing pipeline, our system fuses the information extracted from a pair of patches for more accurate edge classification; (3) a new vote accumulation scheme that robustly localizes objects with curvy boundaries in fragmented edge maps. Our voting scheme produces a probabilistic output for each polyp candidate but unlike the existing methods (e.g., Hough transform) does not require any predefined parametric model of the object of interest; (4) and a unique three-way image representation coupled with convolutional neural networks (CNNs) for classifying the polyp candidates. Our image representation efficiently captures a variety of features such as color, texture, shape, and temporal information and significantly improves the performance of the subsequent CNNs for candidate classification. This contrasts with the exiting methods that mainly rely on a subset of the above image features for polyp detection. Furthermore, this research is the first to investigate the use of CNNs for polyp detection in colonoscopy videos.
The second component of our quality assurance system is an automatic image quality assessment for colonoscopy. The goal is to encourage more diligence during procedures by warning against hasty and low quality colon examination. We detect a low quality colon examination by identifying a number of consecutive non-informative frames in videos. We base our methodology for detecting non-informative frames on two key observations: (1) non-informative frames
most often show an unrecognizable scene with few details and blurry edges and thus their information can be locally compressed in a few Discrete Cosine Transform (DCT) coefficients; however, informative images include much more details and their information content cannot be summarized by a small subset of DCT coefficients; (2) information content is spread all over the image in the case of informative frames, whereas in non-informative frames, depending on image artifacts and degradation factors, details may appear in only a few regions. We use the former observation in designing our global features and the latter in designing our local image features. We demonstrated that the suggested new features are superior to the existing features based on wavelet and Fourier transforms.
The third component of our quality assurance system is a 3D visualization system. The goal is to provide colonoscopists with feedback about the regions of the colon that have remained unexamined during colonoscopy, thereby helping them improve their navigational skills. The suggested system is based on a new 3D reconstruction algorithm that combines depth and position information for 3D reconstruction. We propose to use a depth camera and a tracking sensor to obtain depth and position information. Our system contrasts with the existing works where the depth and position information are unreliably estimated from the colonoscopy frames. We conducted a use case experiment, demonstrating that the suggested 3D visualization system can determine the unseen regions of the navigated environment. However, due to technology limitations, we were not able to evaluate our 3D visualization system using a phantom model of the colon.
Development and use of an iPad-based resuscitation code-blue sheet for improving resuscitation outcomes during intensive patient care
The American Heart Association recommended in 1997 the data elements that should be collected from resuscitations in hospitals. (15) Currently, data documentation from resuscitation events in hospitals, termed ‘code blue’ events, utilizes a paper form, which is institution-specific. Problems with data capture and transcription exists, due to the challenges of dynamic documentation of patient, event and outcome variables as the code blue event unfolds.
This thesis is based on the hypothesis that an electronic version of code blue real-time data capture would lead to improved resuscitation data transcription, and enable clinicians to address deficiencies in quality of care. The primary goal of this thesis is to create an iOS based application, primarily designed for iPads, for code blue events at the Mayo Clinic Hospital. The secondary goal is to build an open-source software development framework for converting paper-based hospital protocols into digital format.
The tool created in this study enabled data documentation to be completed electronically rather than on paper for resuscitation outcomes. The tool was evaluated for usability with twenty nurses, the end-users, at Mayo Clinic in Phoenix, Arizona. The results showed the preference of users for the iPad application. Furthermore, a qualitative survey showed the clinicians perceived the electronic version to be more accurate and efficient than paper-based documentation, both of which are essential for an emergency code blue resuscitation procedure.
There is a strong medical need and important therapeutic applications for improved wireless bioelectric interfaces to the nervous system. Multichannel devices are desired for neural control of robotic prosthetics that interface to remaining nerves in limb stumps of amputees and as alternatives to traditional wired arrays used in for some types of brain stimulation. This present work investigates a new approach to ultrasound-powering of implantable microelectronic devices within the tissue that may better support such applications. These devices are of ultra-miniature size that is enabled by a wireless technique. This study investigates two types of ultrasound-powered neural interfaces for multichannel sensory feedback in neurostimulation. The piezoceramics lead zirconate titanate (PZT) ceramic and polyvinylidene fluoride (PVDF) polymer were the primary materials used to build the devices. They convert ultrasound to electricity that when rectified by a diode produce a current output that is neuro stimulatory to peripheral nerve or the neurons in the brain. Multichannel devices employ a form of spatial multiplexing that directs focused ultrasound towards localized and segmented regions of PVDF or PZT that allows independent channels of nerve actuation. Different frequencies of ultrasound were evaluated for best results. Firstly, a 2.25 MHz frequency signal that is reasonably penetrating through body tissue to an implant several centimeters deep and also a 5 MHz frequency more suited to application for actuation of devices within a less than a centimeter of nerve. Results show multichannel device performance to have a complex inter-relationship with frequency, size and thickness, angular incidence, channel separations, and number of folds (layers connected in series and parallel). The output electrical port impedances of PVDF devices were examined in relationship to that of stimulating electrodes and tissue interfaces. Miniature multichannel devices were constructed using an unreported method of employing state of the art laser cutting systems. The results show that PVDF based devices have advantages over PZT, because of better acoustic coupling with tissue, known better biocompatibility, and better separation between multiple channels. However, the PZT devices proved to be better overall in terms of compactness and higher outputs for a given ultrasound power level.
Detect and analyze the 3-D head movement patterns in marmoset monkeys using wireless tracking system
Head movement is a natural orienting behavior for sensing environmental events around us. Head movement is particularly important for identifying through the sense of hearing the location of an out-of-sight, rear-approaching target to avoid danger or threat. This research aims to design a portable device for detecting the head movement patterns of common marmoset monkeys in laboratory environments. Marmoset is a new-world primate species and has become increasingly popular for neuroscience research. Understanding the unique patterns of their head movements will improve its values as a new primate model for uncovering the neurobiology of natural orienting behavior. Due to their relatively small head size (5 cm in diameter) and body weight (300-500 g), the device has to meet several unique design requirements with respect to accuracy and workability. A head-mount wireless tracking system was implemented based on inertial sensors that are capable of detecting motion in the Yaw, Pitch and Roll axes. The sensors were connected to the encoding station, which transmits wirelessly the 3-axis movement data to the decoding station at the sampling rate of ~175 Hz. The decoding station relays this information to the computer for real-time display and analysis. Different tracking systems, based on the accelerometer and Inertial Measurement Unit is implemented to track the head movement pattern of the marmoset head. Using these systems, translational and rotational information of head movement are collected, and the data analysis focuses on the rotational head movement in body-constrained marmosets. Three stimulus conditions were tested: 1) Alert, 2) Idle 3) Sound only. The head movement patterns were examined when the house light was turned on and off for each stimulus. Angular velocity, angular displacement and angular acceleration were analyzed in all three axes.
Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior.