Advances in non-invasive biosensing measures to monitor wound healing progression.

Impaired wound healing is a significant financial and medical burden. The synthesis and deposition of extracellular matrix (ECM) in a new wound is a dynamic process that is constantly changing and adapting to the biochemical and biomechanical signaling from the extracellular microenvironments of the wound. This drives either a regenerative or fibrotic and scar-forming healing outcome. Disruptions in ECM deposition, structure, and composition lead to impaired healing in diseased states, such as in diabetes. Valid measures of the principal determinants of successful ECM deposition and wound healing include lack of bacterial contamination, good tissue perfusion, and reduced mechanical injury and strain. These measures are used by wound-care providers to intervene upon the healing wound to steer healing toward a more functional phenotype with improved structural integrity and healing outcomes and to prevent adverse wound developments. In this review, we discuss bioengineering advances in 1) non-invasive detection of biologic and physiologic factors of the healing wound, 2) visualizing and modeling the ECM, and 3) computational tools that efficiently evaluate the complex data acquired from the wounds based on basic science, preclinical, translational and clinical studies, that would allow us to prognosticate healing outcomes and intervene effectively. We focus on bioelectronics and biologic interfaces of the sensors and actuators for real time biosensing and actuation of the tissues. We also discuss high-resolution, advanced imaging techniques, which go beyond traditional confocal and fluorescence microscopy to visualize microscopic details of the composition of the wound matrix, linearity of collagen, and live tracking of components within the wound microenvironment. Computational modeling of the wound matrix, including partial differential equation datasets as well as machine learning models that can serve as powerful tools for physicians to guide their decision-making process are discussed.

EMvelop stimulation: minimally invasive deep brain stimulation using temporally interfering electromagnetic waves.

Objective.Recently, the temporal interference stimulation (TIS) technique for focal noninvasive deep brain stimulation (DBS) was reported. However, subsequent computational modeling studies on the human brain have shown that while TIS achieves higher focality of electric fields than state-of-the-art methods, further work is needed to improve the stimulation strength. Here, we investigate the idea of EMvelop stimulation, a minimally invasive DBS setup using temporally interfering gigahertz (GHz) electromagnetic (EM) waves. At GHz frequencies, we can create antenna arrays at the scale of a few centimeters or less that can be endocranially implanted to enable longitudinal stimulation and circumvent signal attenuation due to the scalp and skull. Furthermore, owing to the small wavelength of GHz EM waves, we can optimize both amplitudes and phases of the EM waves to achieve high intensity and focal stimulation at targeted regions within the safety limit for exposure to EM waves.Approach.We develop a simulation framework investigating the propagation of GHz EM waves generated by line current antenna elements and the corresponding heat generated in the brain tissue. We propose two optimization flows to identify antenna current amplitudes and phases for either maximal intensity or maximal focality transmission of the interfering electric fields with EM waves safety constraint.Main results.A representative result of our study is that with two endocranially implanted arrays of size4.2 cm×4.7 cmeach, we can achieve an intensity of 12 V m-1with a focality of3.6 cmat a target deep in the brain tissue.Significance.In this proof-of-principle study, we show that the idea of EMvelop stimulation merits further investigation as it can be a minimally invasive way of stimulating deep brain targets and offers benefits not shared by prior methodologies of electrical or magnetic stimulation.

An Integrated Microheater Array With Closed-Loop Temperature Regulation Based on Ferromagnetic Resonance of Magnetic Nanoparticles.

Magnetic nanoparticles (MNP) can generate localized heat in response to an external alternating magnetic field, a unique capability that has enabled a wide range of biomedical applications. Compared with other heating mechanisms such as dielectric heating and ohmic heating, MNP-based magnetic heating offers superior material specificity and minimal damage to the surrounding environment since most biological systems are non-magnetic. This paper presents a first-of-its-kind fully integrated magnetic microheater array based on the ferromagnetic resonance of MNP at Gigahertz (GHz) microwave frequencies. Each microheater pixel consists of a stacked oscillator to actuate MNP with a high magnetic field intensity and an electro-thermal feedback loop for precise temperature regulation. The four-stacked/five-stacked oscillator achieves >19.5/26.5 Vpp measured RF output swing from 1.18 to 2.62 GHz while only occupying a single inductor footprint, which eliminates the need for additional RF power amplifiers for compact pixel size (0.6 mm × 0.7 mm) and high dc-to-RF energy efficiency (45%). The electro-thermal feedback loop senses the local temperature and enables closed-loop temperature regulation by controlling the biasing voltage of the stacked oscillator, achieving a measured maximum/RMS temperature error of 0.53/0.29 °C. In the localized heating demonstration, two PDMS membranes mixed with and without MNP are attached to the microheater array chip, respectively, and their surface temperatures are monitored by an infrared (IR) camera. Only the area above the inductor (∼0.03 mm2) is efficiently heated up to 43 °C for the MNP-PDMS membrane, while the baseline temperature stays <37.8 °C for the PDMS membrane without MNP.

Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries.

Mild traumatic brain injuries (mTBIs) are the most common type of brain injury. Timely diagnosis of mTBI is crucial in making 'go/no-go' decision in order to prevent repeated injury, avoid strenuous activities which may prolong recovery, and assure capabilities of high-level performance of the subject. If undiagnosed, mTBI may lead to various short- and long-term abnormalities, which include, but are not limited to impaired cognitive function, fatigue, depression, irritability, and headaches. Existing screening and diagnostic tools to detect acute andearly-stagemTBIs have insufficient sensitivity and specificity. This results in uncertainty in clinical decision-making regarding diagnosis and returning to activity or requiring further medical treatment. Therefore, it is important to identify relevant physiological biomarkers that can be integrated into a mutually complementary set and provide a combination of data modalities for improved on-site diagnostic sensitivity of mTBI. In recent years, the processing power, signal fidelity, and the number of recording channels and modalities of wearable healthcare devices have improved tremendously and generated an enormous amount of data. During the same period, there have been incredible advances in machine learning tools and data processing methodologies. These achievements are enabling clinicians and engineers to develop and implement multiparametric high-precision diagnostic tools for mTBI. In this review, we first assess clinical challenges in the diagnosis of acute mTBI, and then consider recording modalities and hardware implementation of various sensing technologies used to assess physiological biomarkers that may be related to mTBI. Finally, we discuss the state of the art in machine learning-based detection of mTBI and consider how a more diverse list of quantitative physiological biomarker features may improve current data-driven approaches in providing mTBI patients timely diagnosis and treatment.

Recent Advances in Electrical Neural Interface Engineering: Minimal Invasiveness, Longevity, and Scalability.

Electrical neural interfaces serve as direct communication pathways that connect the nervous system with the external world. Technological advances in this domain are providing increasingly more powerful tools to study, restore, and augment neural functions. Yet, the complexities of the nervous system give rise to substantial challenges in the design, fabrication, and system-level integration of these functional devices. In this review, we present snapshots of the latest progresses in electrical neural interfaces, with an emphasis on advances that expand the spatiotemporal resolution and extent of mapping and manipulating brain circuits. We include discussions of large-scale, long-lasting neural recording; wireless, miniaturized implants; signal transmission, amplification, and processing; as well as the integration of interfaces with optical modalities. We outline the background and rationale of these developments and share insights into the future directions and new opportunities they enable.

Intracellular cardiomyocytes potential recording by planar electrode array and fibroblasts co-culturing on multi-modal CMOS chip.

Intracellular action potential signals reveal enriched physiological information. Patch clamp techniques have been widely used to measure intracellular potential. Despite their high signal fidelity, they suffer from low throughput. Recently, 3D nanoelectrodes have been developed for intracellular potential recording. However, they are limited by scalability, yield, and cost, directly constraining their use in monitoring large number of cells and high throughput applications. In this paper, we demonstrate intracellular potential monitoring of cardiomyocytes using simple 2D planar electrode array in a standard CMOS process without patch clamps or post fabricated 3D nanoelectrodes. This is enabled by our unique cardiomyocytes/fibroblasts co-culturing technique and electroporation. The co-cultured fibroblasts promote tight sealing of cardiomyocytes on electrodes and enable high-fidelity intracellular potential monitoring based on 2D planar electrode. Compared to existing technologies, our platform has a unique potential to achieve an unprecedented combination of throughput, spatiotemporal resolution, and a tissue-level field-of-view for cellular electrophysiology monitoring.

Multi-parametric cell profiling with a CMOS quad-modality cellular interfacing array for label-free fully automated drug screening.

Cells are complex systems with concurrent multi-physical responses, and cell physiological signals are often encoded with spatiotemporal dynamics and further coupled with multiple cellular activities. However, most existing electronic sensors are only single-modality and cannot capture multi-parametric cellular responses. In this paper, a 1024-pixel CMOS quad-modality cellular interfacing array that enables multi-parametric cell profiling for drug development is presented. The quad-modality CMOS array features cellular impedance characterization, optical detection, extracellular potential recording, and biphasic current stimulation. The fibroblast transparency and surface adhesion are jointly monitored by cellular impedance and optical sensing modalities for comprehensive cell growth evaluation. Simultaneous current stimulation and opto-mechanical monitoring based on cardiomyocytes are demonstrated without any stimulation/sensing dead-zone. Furthermore, drug dose-dependent multi-parametric feature extractions in cardiomyocytes from their extracellular potentials and opto-mechanical signals are presented. The CMOS array demonstrates great potential for fully automated drug screening and drug safety assessments, which may substantially reduce the drug screening time and cost in future new drug development.

Interdigitated microelectronic bandage augments hemostasis and clot formation at low applied voltage in vitro and in vivo.

Hemorrhage or uncontrolled bleeding can arise either due to a medical condition or from a traumatic injury and are typically controlled with the application of a hemostatic agent. Hemostatic agents are currently derived from animal or human products, which carry risks of blood borne infections and immune dysregulation. Therefore, the need exists for novel biomedical therapies not derived from animal or human products to achieve hemostasis. Accordingly, we created an interdigitated microelectronic bandage that applies low voltage electrical stimulation to an injury site, resulting in faster clot formation without excessive heating, accelerated fibrin formation, and hemostasis overall. Our interdigitated microelectronic bandage found fibrin formed 1.5× faster in vitro. In vivo, total cessation of bleeding was 2.5× faster, resulting in 2× less blood loss. Electricity has been used in medical applications such as defibrillation, cauterization, and electrosurgery, but scant research has focused on hemostasis. Here we report a novel surface treatment using an interdigitated microelectronic device that creates rapid hemostasis in both in vitro and in vivo bleeding models with low applied voltages, representing a new and novel class of hemostatic agents that are electrically-based.

1024-Pixel CMOS Multimodality Joint Cellular Sensor/Stimulator Array for Real-Time Holistic Cellular Characterization and Cell-Based Drug Screening.

This paper presents a fully integrated CMOS multimodality joint sensor/stimulator array with 1024 pixels for real-time holistic cellular characterization and drug screening. The proposed system consists of four pixel groups and four parallel signal-conditioning blocks. Every pixel group contains 16 × 16 pixels, and each pixel includes one gold-plated electrode, four photodiodes, and in-pixel circuits, within a pixel footprint. Each pixel supports real-time extracellular potential recording, optical detection, charge-balanced biphasic current stimulation, and cellular impedance measurement for the same cellular sample. The proposed system is fabricated in a standard 130-nm CMOS process. Rat cardiomyocytes are successfully cultured on-chip. Measured high-resolution optical opacity images, extracellular potential recordings, biphasic current stimulations, and cellular impedance images demonstrate the unique advantages of the system for holistic cell characterization and drug screening. Furthermore, this paper demonstrates the use of optical detection on the on-chip cultured cardiomyocytes to real-time track their cyclic beating pattern and beating rate.

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 µm × 100 µm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.