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A total of 160 oblique impact tests were performed to study the relationship between the kinematic response of a helmeted headform and the impact severity caused by a change in speed (Group 1) and anvil angle (Group 2). In this study, the kinematic response of a helmeted headform was evaluated by measuring its linear acceleration, rotational acceleration, and rotational velocity. In Group 1, a football helmet was tested at 45° anvil angle at four different impact speeds ranging from 4.5 to 7.4 m/s on five impact locations. The results showed that, for all cases, the relationship between the impact speed and helmeted headform kinematic response was linear, with an average R2 value of 0.98. At each impact location, a prediction line was generated using the data points for the lowest and highest speeds. For the speeds of 5.5 and 6.5 m/s, the prediction of the helmeted headform kinematic response was validated with an average error of 4.7%. In Group 2, the helmeted headform was tested at 5.5 m/s impact speed at six different anvil angles between 15° and 55°, and the response was fitted with a second-degree polynomial (curve) with an average R2 value of 0.96. The kinematic response of the higher and lower impact speeds was obtained experimentally for one angle, and the fitted curve for 5.5 m/s was offset to pass through the obtained kinematic response. The predicted helmeted headform kinematic response was experimentally validated, and the average error was found to be 8.3%. The results showed that it is possible to predict the kinematic response of a helmeted headform by interpolating or extrapolating the data without having to perform an additional impact test. An analysis of other research works also showed similar predictable behaviour for headform equipped with other helmet models. Therefore, the number of tests during the process of evaluating helmet performance can be reduced.

Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to assess its optical properties and identify abnormalities. DOT image reconstruction is an ill-posed problem due to the highly scattered photons in the medium and the smaller number of measurements compared to the number of unknowns. Limited-angle DOT reduces probe complexity at the cost of increased reconstruction complexity. Reconstructions are thus commonly marred by artifacts and, as a result, it is difficult to obtain an accurate reconstruction of target objects, e.g., malignant lesions. Reconstruction does not always ensure good localization of small lesions. Furthermore, conventional optimization-based reconstruction methods are computationally expensive, rendering them too slow for real-time imaging applications. Our goal is to develop a fast and accurate image reconstruction method using deep learning, where multitask learning ensures accurate lesion localization in addition to improved reconstruction. We apply spatial-wise attention and a distance transform based loss function in a novel multitask learning formulation to improve localization and reconstruction compared to single-task optimized methods. Given the scarcity of real-world sensor-image pairs required for training supervised deep learning models, we leverage physics-based simulation to generate synthetic datasets and use a transfer learning module to align the sensor domain distribution between in silico and real-world data, while taking advantage of cross-domain learning. Applying our method, we find that we can reconstruct and localize lesions faithfully while allowing real-time reconstruction. We also demonstrate that the present algorithm can reconstruct multiple cancer lesions. The results demonstrate that multitask learning provides sharper and more accurate reconstruction.

Identifying breast cancer lesions with a portable diffuse optical tomography (DOT) device improves early detection, while avoiding otherwise unnecessarily invasive, ionizing, and expensive modalities such as CT, as well as enabling first line of care treatment efficacy. Critical to this capability is not just identification of lesions, but rather the complex problem of discriminating between malignant and benign lesions. To accurately capture the highly heterogeneous tissue of a cancer lesion embedded in healthy breast tissue with non-invasive DOT, multiple frequencies can be combined to optimize signal penetration and reduce sensitivity to noise. However, these frequency responses can overlap, capture common information, and correlate, potentially confounding reconstruction and downstream end tasks. We show that an orthogonal fusion loss of multi-frequency DOT can improve reconstruction. More importantly, the orthogonal fusion leads to more accurate end-to-end identification of malignant versus benign lesions, illustrating its regularization properties on the multi-frequency input space. With the line-of-care deployment of portable DOT probes requiring a severely constrained computational budget, we show that our raw-to-task model, for direct prediction of end task from signal, significantly reduces computational complexity without sacrificing accuracy, enabling lower latency and higher, real-time throughput in medical settings.

Tissue classification based upon tissue stiffness is very useful in early diagnosis of cancer; specifically, breast tissue health is diagnosed through tissue stiffness. This paper proposes a method to define the mechanical characteristics of various soft tissues, which could be helpful in discovery of soft tissue abnormalities. This study focused on tissue characterization and the identification of the relationship between tissue properties and pathological mechanics using an elastography technique (method of cancer detection, that uses the response of soft tissue to deformation) based on the Yeoh hyper-elastic model. The suitability of the Yeoh model was validated through compression testing of breast phantoms, animal tissues, and in vivo human tissues. The mean deviation between the known and calculated position was 0.31 ± 0.16 mm. The maximum deviation was less than 0.86 mm. The results indicate that the location of a scintillator within the recording cage imaged with two cameras can be calculated with submillimeter accuracy. We hope that our methods can be applied to improve automatic (even real-time) tracking of various animals in vivo.

We report, for the first time, a robust angular rate sensor that is operated at 2:1 Autoparametric Resonance (AR) with a wide frequency bandwidth at 3dB amplitude drop of 320.7 Hz. The sensor utilizes inherent forcing and inertial or elastic nonlinearities arising from electrostatic forces and fabrication imperfections respectively, to excite the sense mode via 2:1 AR causing a wider frequency response of the sense mode. The sensor is actuated electrostatically, and its output is sensed using variable gap capacitive electrodes. The sensor is tested on a rate table and a maximum scale factor of $38.99\ \mu \mathrm{V}/^{\circ}/\mathrm{s}$ with a full-scale nonlinearity of 1.2%, dynamic range of ±270 °/s, and noise density of 0.042 °/s/√Hz are measured.

Most breast cancer lesions absorb higher levels of near-infrared (NIR) radiation compared to healthy breast tissue due to its increased vascularity. Oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) primarily found in cancerous vascular lesions, absorbs higher levels of radiation in the 650 nm to 850 nm wavelength range than the surrounding fatty tissue and water in the human breast. NIR diffuse optical spectroscopy (DOS) provides real-time functional and compositional information based on the optical properties of biological tissues, which cannot be accomplished by other portable breast imaging modalities. Here we present the first set of clinical trials using a non-invasive, hand-held diffuse optical breast scanner (DOB-Scan probe3) to capture in vivo cross-sectional images of the breast. The scanner uses four NIR illuminating sources with different wavelengths, 690 nm, 750 nm, 800 nm, and 850 nm, to determine the concentrations of the four main constituents of breast tissue, oxy-hemoglobin (HbO2), deoxy-hemoglobin (Hb), water (H2O), and fat. In this paper, we briefly explain the hardware design and image reconstruction algorithm of the DOB-Scan probe, the data collection process, and the imaging results of four different participants, selected from twenty, all who are diagnosed with breast cancer. For each patient, images were scanned from two locations, the first over the cancerous lesion and the second over the same region on the contralateral healthy breast, as a means of establishing controls for comparison. During each scan, four cross-sectional images of the breast, corresponding to four different NIR wavelengths, are reconstructed and displayed on a user interface for reference. Clinical results confirm that the absorption coefficients of cancerous lesions are significantly higher than the normal surrounding tissue. We propose to deploy the probe to effectively identify cancerous breast tissue at an early stage in a primary care setting, which could increase the efficiency of screening programs.

This paper reports on the design, fabrication and rate table characterization of an H-shaped tuning fork microresonator with 2:1 internal resonance as an actuation mechanism. The nonlinear principle of operation addresses major challenges in MEMS Coriolis vibratory gyroscopes: eliminating the mode-matching requirement, minimizing instability and drift due to mechanical cross-coupling between the fundamental modes, and generating a wide operating frequency range with high-signal gain and less sensitivity to fluctuations in driving frequency. The rate measurement relies on capturing the half-order subharmonic response of the device while undergoing the angular velocity. The micromachined resonator is fabricated using the MEMS Integrated Design for Inertial Sensors platform offered by Teledyne DALSA Inc. The experimental finding demonstrated the prominent M-shaped nonlinear resonant curves due to a frequency ratio close to 2:1. The microresonator is nominally operated in the overlap region between the forward and backward frequency sweeps, where the signal gain is less sensitive to frequency fluctuations. The microresonator described here operates at 561.23600kHz in a near 2:1 frequency ratio between two anti-phase resonant modes. Experimental rate characterization of the microresonator revealed a linear dynamic range of 220 deg sec-1 with a sensitivity of 0.011 mV deg-1 sec-1 using an 80V DC polarization voltage. The experimental results of the microresonator showed the induced oscillations in the so-called pendulum mode by Coriolis force coupling, despite a clear disparity on natural frequencies of the desired modes.

An electrical Impedance based tool is designed and developed to aid physicians performing clinical exams focusing on cancer detection. Current research envisions improvement in sensor-based measurement technology to differentiate malignant and benign lesions in human subjects. The tool differentiates malignant anomalies from nonmalignant anomalies using Electrical Impedance Spectroscopy (EIS). This method exploits cancerous tissue behavior by using EIS technique to aid early detection of cancerous tissue. The correlation between tissue electrical properties and tissue pathologies is identified by offering an analysis technique based on the Cole model. Additional classification and decision-making algorithm is further developed for cancer detection. This research suggests that the sensitivity of tumor detection will increase when supplementary information from EIS and built-in intelligence are provided to the physician.

Recently, micro electro-mechanical systems (MEMS) inertial sensors have found their way in various applications. These sensors are fairly low cost and easily available but their measurements are noisy and imprecise, which poses the necessity of calibration. In this paper, we present an approach to calibrate an inertial measurement unit (IMU) comprised of a low-cost tri-axial MEMS accelerometer and a gyroscope. As opposed to existing methods, our method is truly infield as it requires no external equipment and utilizes gravity signal as a stable reference. It only requires the sensor to be placed in approximate orientations, along with the application of simple rotations. This also offers easier and quicker calibration comparatively. We analyzed the method by performing experiments on two different IMUs: an in-house built IMU and a commercially calibrated IMU. We also calibrated the in-house built IMU using an aviation grade rate table for comparison. The results validate the calibration method as a useful low-cost IMU calibration scheme.

This paper reports on the design and characterization of an $H$ -shaped microresonator exhibiting nonlinear modal interactions due to 2:1 internal resonance. This has been made possible through careful design of the structure with attention to the limits of microfabricated devices. The intended nonlinear dynamics rely on the continuous transfer of energy between the anti-phase motions of two $H$ -like proof masses of the device to a mode along the orthogonal direction. Finite element and reduced order models of the structure were developed and used to design the devices with two desired flexural modes in a ~2:1 frequency ratio. The microresonator was fabricated in a commercial foundry process. Extensive experiments and transient simulations were conducted to verify the desired nonlinear responses and the models. It was demonstrated that the low-frequency mode of the device was excited through auto-parametric excitation of the higher frequency mode when the excitation level exceeded a specific threshold as expected. The device design methodologies can be employed to fabricate various sensors, including nonlinear Coriolis vibratory gyroscopes incorporating 2:1 internal resonance. [2017-0035]

Xerostomia, or dry mouth syndrome, is one of the radiation therapy (RT)-induced side effects experienced by head and neck cancer patients. Measuring the severity of xerostomia can be performed by several techniques such as measuring the differential weight of dental rolls placed in the mouth for a fixed time period, measuring the electromyographic activity of musculus digastricus, using parotid cup, and electrophysiological measurements by electrical impedance. The present study focuses on detecting the change in bioimpedance around the oral cavity when salivation is induced using lime juice on healthy human subjects. In this study, impedance changes between stimulated and resting states of the salivary glands for 31 healthy volunteers were measured and analyzed. Pre- and post-stimulation impedance measurement was performed on healthy volunteer subjects using impedance spectroscopy over 50 frequencies ranging from 10 kHz to 1 MHz. The electrical properties of salivary glands were extracted by fitting the measured admittance data to the well-known Cole model. Comparison of measured electrical properties of gland at the resting and stimulated states reveals the changes in the intra- and extra-cellular spaces of salivary gland as a result of saliva secretion. Statistical analysis of the spectroscopy data collected shows that there is a significant difference in electrical properties of tissue between resting and stimulated states of the salivary activity. These electrical impedance spectroscopy measurements will be used to benchmark changes of impedance due to salivary gland stimulation.

Formation of membrane pinholes is a common defect in fuel cells, inflicting more cost and making less durable cells. This work focuses on mitigating this issue, and offers a continuous online treatment instead of attempting to dynamically model the hydrogen transfer leak rate. This is achieved by controlling the differential pressure between the anode and cathode compartments at the inlet side of the fuel cell stack, known as the fuel overpressure. The model predictive control approach is used to attain the objectives in a Ballard 9-cell Mk1100 polymer electrolyte membrane fuel cell (PEMFC) with inclusion of hydrogen transfer leak. Furthermore, the pneumatic modeling technique is used to model the entire anode side of a fuel cell station. The hydrogen transfer leak is embedded in the model in a novel way, and is considered as a disturbance during the controller design. Experimental results for different sizes of hydrogen transfer leaks are provided to show the benefits of fuel overpressure control system in alleviating the effects of membrane pinholes, which in turn increases membrane longevity, and reduces hydrogen emissions in the eventual presence of transfer leaks. Moreover, the model predictive controller provides an optimal control input while satisfying the problem constraints.

This paper focuses on the design of a tuning fork microresonator that utilizes its inherent inertial nonlinearities for its operation. Two orthogonal in-plane modes of the microresonator are carefully designed so that the natural frequency ratio between the higher and the lower frequency modes is close to two. When we electrostatically excite the higher frequency mode with the excitation voltage higher than some threshold, the lower frequency mode gets autoparametrically excited due to a nonlinear resonance phenomenon known as two-to-one (2:1) internal resonance. We employed the MEMS Integrated Design for Inertial Sensors (MIDIS), a high vacuum bulk-micromachining process, by Teledyne Dalsa to fabricate the proposed microresonator. We then experimentally demonstrate the 2:1 internal resonance phenomenon occurring in the resonator and highlight its applicability in developing the resonating MEMS based sensors.

To mitigate the injurious effect of the rotational acceleration of the brain, a modular Impact Diverting Mechanism (IDM) has been developed. The IDM can replace stickers (decals) that normally attach to the exterior of a football helmet. The IDM decals reduce friction and catch points between the covered area with the IDM on the outer shell of the helmet and the impacting surface, thereby decreasing rotational acceleration acting on the player’s head. A Riddell Speed helmet’s exterior was prepared with the IDM and outfitted to a headform equipped with linear accelerometers and gyroscopes. The helmets were tested at an impact velocity of 5.5 m/s at 15°, 30°, and 45° to the vertical: on the front, side, and back of the helmet. Results of 135 impact tests in the lab show that the IDM decal, when compared to helmets without it, reduced the rotational acceleration, rotational velocity, SI, HIC, and RIC ranging from 22% to 77%, 20% to 74%, 13% to 68%, 7% to 68%, 31% to 94%, respectively. Protection against rotational acceleration from oblique impacts is not prioritized in modern football helmets, as evident by current standard helmet testing protocols. This study demonstrates that the inclusion of the IDM decals in football helmets can help reduce the effects of rotational acceleration of the head during oblique impacts.

Micro- and nano-resonators have been studied extensively both for the scientific viewpoint to understand basic interactions at small scales as well as for applied research to build sensors and mechanical signal processors. Majority of the resonant microsystems, particularly those manufactured at a large scale, have employed simple mechanical structures with one dominant resonant mode, such as in timing resonators, or linearly coupled resonant modes, as in vibratory gyroscopes. There is an increasing interest in the development of models and methods to better understand the nonlinear interactions at micro- and nano-scales and also to potentially improve the performance of the existing devices in the market beyond limits permissible by the linear effects. Internal resonance is a phenomenon that allows for nonlinear coupling and energy transfer between different vibration modes of a properly designed system. Herein, for the first time, we describe and experimentally demonstrate the potential for employing internal resonance for detection of angular rate signals, where the Coriolis effect modifies the energy coupling between the distinct drive and sense vibration modes. In doing so, in addition to providing a robust method of exciting the desired mode, the proposed approach further alleviates the mode-matching requirements and reduces instabilities due to the cross-coupling between the modes in current linear vibratory gyroscopes.

Diffuse optical spectroscopy is a relatively new, noninvasive and nonionizing technique for breast cancer diagnosis. In the present study, we have introduced a novel handheld diffuse optical breast scan (DOB-Scan) probe to measure optical properties of the breast in vivo and create functional and compositional images of the tissue. In addition, the probe gives more information about breast tissue’s constituents, which helps distinguish a healthy and cancerous tissue. Two symmetrical light sources, each including four different wavelengths, are used to illuminate the breast tissue. A high-resolution linear array detector measures the intensity of the back-scattered photons at different radial destinations from the illumination sources on the surface of the breast tissue, and a unique image reconstruction algorithm is used to create four cross-sectional images for four different wavelengths. Different from fiber optic-based illumination techniques, the proposed method in this paper integrates multi-wavelength light-emitting diodes to act as pencil beam sources into a scattering medium like breast tissue. This unique design and its compact structure reduce the complexity, size and cost of a potential probe. Although the introduced technique miniaturizes the probe, this study points to the reliability of this technique in the phantom study and clinical breast imaging. We have received ethical approval to test the DOB-Scan probe on patients and we are currently testing the DOB-Scan probe on subjects who are diagnosed with breast cancer.