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Research goal

The main goal of our research program is to help maintain and improve health by providing medical doctors, biomedical researchers and/or patients with novel microelectronic technologies for miniature medical devices that directly or indirectly interface with the human body in order to monitor its function and, in some cases, influence it. We also target scientific, industrial, consumer and environmental sensory electronics applications.

Motivation

Modern healthcare practices suggest that patient-interfacing medical devices of the future are to be potent, ubiquitous, and inexpensive. Our research investigates such medical devices. These devices address specific unmet healthcare needs, particularly those in medical monitoring, diagnostics and therapy in clinics, biomedical research labs and at home. Of our immediate interest are applications in neuroscience and molecular biology. We target disorders and diseases with limited conventional treatment options or with costly diagnostics options. Specific medical applications include electronic therapy for intractable epilepsy [J21, C51, C56, J13] and electronic screening for early detection of certain types of cancer [C45, C50, J16, J27, J28, J11, J15, J24].

Approach

Interfacing with the human body for the purpose of maintaining or improving health requires a variety of sensory functionalities. These can be as simple as monitoring key vital signs, or as complex as monitoring electrochemical activity of the brain or examining biochemical content of bodily fluids. In our research we target applications where novel implantable, wearable or disposable biomedical devices with complex sensory functions are uniquely enabled by low-cost integrated circuit (IC) technologies such as CMOS.

Specifically, we focus on the design of integrated circuits, VLSI architectures and signal-processing algorithms that comprise the core of a sensory medical device. Such sensory devices not only acquire raw sensory data, but also perform local sensory signal processing (such as feature extraction and machine learning data classification algorithms), and provide feedback information or, in some cases, feedback action as shown in Figure 1. One successful example of such a system is a single-chip brain implant for treatment of intractable epilepsy we developed that accurately detects early seizures and automatically triggers neuro-stimulation to effectively control them [J21, C51, C56].

Figure 1. Functional block diagram of a biomedical sensory microsystem.

Key challenges

From the system integration perspective, for potency, ubiquity and low cost it is often advantageous to utilize sensory properties of the integrated circuits themselves or additional small sensors of a similar form-factor, without bulky externally connected sensors or associated packaging costs. In our previous work, we have demonstrated suitability of silicon integrated circuits (ICs) to be further integrated (post-CMOS) with various arrays of on-die sensors for implantable, wearable and disposable microsystem implementations. These include: implantable arrays of micro-needles to monitor spatial maps of electrical neural activity in the brain for epileptic seizure propagation studies [J9, C27, J26, J7, J12, J25] (e.g., in Figure 2, left); arrays of gold microelectrodes to electrochemically measure concentration of neurochemicals for brain chemistry studies [J35, J17, C37, J5] or DNA concentration for cancer screening [C45, C50, J16, J27, J28] (e.g., in Figure 2, middle); and photo-detector arrays for optical contact-imaging of various micro-scale biological objects such as fluorescently labeled DNA microarrays [J11, J15, J18, J23, J24] (e.g., in Figure 2, right).

Figure 2. Examples of system integration solutions with on-silicon sensors.

From the front-end circuits perspective, the key challenges are low signal-to-noise ratio, signal offset and drift, high interference levels, intrinsic electronic noise, time-varying signal source properties, various artifacts and numerous other sensory interface-related issues. In our previous work, we have addressed these issues individually by sensory transducer innovations (e.g., novel photodetectors [J15, J23]) and various integrated circuit design solutions (e.g., novel signal filtering circuits [J6, J20] and novel chopping circuits [J19, J23]). Our latest projects include optical sensors for computational photography, electro-physiological sensors for brain activity monitoring and modulation as well as electro-chemical sensors for molecular diagnostics and neurochemistry monitoring.

From the back-end circuits perspective, the key challenges are the ever-growing requirements for higher sensory signal processing throughput and higher integration density with a limited power budget. Power budget is often constrained by heat dissipation (such as that into the surrounding tissue). In our previous work, we have developed a number of circuit design techniques that break the conflicting throughput-area-power trade-offs. These include various analog-to-digital converter architectures that perform computationally-expensive signal processing operation such as multiplication without a significant resource overhead and requiring no power- or area-hungry digital multipliers [J6, J10, J16, J20], as well as novel energy-efficient signal processing mixed-signal VLSI architectures [J8, J13, J14, J20], low-power RF transceivers [J20, J21, J27, C45, C50], and wireless energy transfer [C55]. Within this thrust, we are currently pursuing research in energy-efficient digital and mixed-signal accelerators for high-performance machine learning and artificial intelligence applications, computing architectures co-integrated with sensory arrays, as well as data and energy transfer with on-CMOS inductive coils.