Seyedabdollah Mirbozorgi

Inspired by the human cognitive process and memory capabilities, we present a novel vision transformer (ViT) in this paper, called G ate G uided T ransformer (G2T) for medical image segmentation. G2T addresses a key limitation of cascaded decoder blocks in vision transformers; that is their difficulty in retaining and propagating important information from earlier stages, which often leads to suboptimal feature decoding in later blocks. Our proposed G2T has (i) a novel feature-aware decoder (FAD) consisting of three convolutional gates named Refine, Expand, and Produce (REP), which deal with forgetting irrelevant features, remembering relevant features, and generating the output features, respectively; (ii) a novel attention mixing module called LH-RAAM (Low to High-Resolution Attention Accumulation Module) that accumulates attentions computed in the encoder blocks from low-level features to high-level features, and aggregates them with the attentions computed in the decoder blocks to emphasize similar features during both the encoding and decoding stages. Evaluated on six medical imaging datasets, G2T consistently outperforms existing state-of-the-art models by 1-3%, achieving a 94.67% mean Dice score ±0.01 standard deviation on the ACDC dataset and 92.90% ±0.02 on the Synapse dataset. Ablation studies additionally justify the utility of each component of G2T along with strong generalizability outside the medical domain.

We present in this paper an implantable closed-loop neuromodulation prototype system for type 2 diabetes (T2D) management, which leverages pancreatic electrophysiology as both a sensing and therapeutic modality. Among candidate biomarkers, the fraction of plateau phase (FOPP) emerges as a robust indicator of glucose dynamics. Hence, the neural interface is optimized for low-power measurement of the electrical activity of the beta-cells with high accuracy in direct readout mode and long-term monitoring in FOPP mode. The experimental framework was established using a perfused pancreas model, first in mice and then optimized for rats, with glucose-dependent signals captured via a custom 16-channel neural interface. Results confirmed the feasibility of extracting FOPP in ex vivo settings, though signal complexity differed from isolated islets in vitro. Additionally, a fabricated 8-channel electrical stimulator with adjustable current levels and optimized charge balancing technique, demonstrated the capability to meet physiological requirements for beta-cell activation. While integration of AI-based classifiers for advanced FOPP–glucose correlation remains a future step, this study establishes the foundational experimental and technological evidence for a next-generation closed-loop neuromodulator.

Photobiomodulation (PBM) therapy using red- and near-infrared (NIR) light has shown beneficial regenerative effects on cell functionalities and consequently on health applications. Light parameter values, particularly power density, significantly affect the treatment outcomes. The limited use of light in transcutaneous applications is due to the power attenuation challenge, which restricts the transmission of light energy to deeper tissues. However, the potential of light therapy to restore cellular function presents a promising strategy for regenerating cells of internal human organs. We have 1) studied the mechanism and impact of red light at the cellular level, 2) reviewed the literature and classified the research done using light therapy, indicating the positive and negative effects associated with the light power density and exposure time levels, and 3) proposed a design rule for designing PBM implants targeting interior organs. Therefore, this work leads to 1) designing safe and efficient implantable devices by extracting the necessary light parameters, and 2) expanding the applications of light therapy. The range of the red-light power density used in different studies starts from 10 mW/cm² to as big as 5000 mW/cm² in a few cases, and from 10 s to 3000 s for different exposure times. According to the light parameters, we have tested different types of off-the-shelf LEDs to experimentally find the correlation between the generated light power densities at different distances from light sources and the LEDs’ input electrical power. We have found that for an average light power density of 100 mW/cm² over an area of 1 cm², the input power of 18 mW must be delivered to the LED, which is achievable safely via wireless inductive links for delivering sufficient power deep in the body with under 1.6 W/kg of specific absorption rate (SAR). A design rule and approach are provided in this work as a starting point for designing PBM implants.

This chapter introduces a motorized camera system designed for monitoring and evaluating the tests of the Short Physical Performance Battery (SPPB). This system targets physical performance assessment for older patients undergoing cancer treatment. The device is self-contained, incorporating a small computer, three cameras, and two motors. The core algorithms utilize three object recognition techniques: template matching, Haar cascades, and Channel and Spatial Reliability Tracking. To facilitate user interaction, graphical user interfaces (GUIs) are developed on the small computer, enabling test execution and camera adjustments via cell phone and its hotspot. The system delivers precise results, with gait speed tests showing a range of 0.041–1.92 m/s and average speed and distance accuracies exceeding 95%. The standing balance and 5 times sit-stand (5TSS) tests achieve average time accuracies exceeding 97%. This novel camera-based device holds promise in enhancing evaluation of lower body extremity fitness for elderly people receiving cancer health care, offering a reliable and efficient solution for monitoring their progress and well-being.

This paper presents an innovative T/Y-maze-based wireless power transmission (WPT) system designed to monitor spatial reference memory and learning behavior in freely moving rats. The system facilitates uninterrupted optical/electrical stimulation and neural recording experiments through the integration of wireless headstages or implants in T/Y maze setups. Utilizing an array of resonators covering the entire underneath of the mazes, the wireless platform ensures scalability with various configurations. The array is designed to ensure a natural localization mechanism to localize the Tx power toward the location of the Rx coil. The system is analyzed and modeled using ANSYS HFSS software to optimize design. The primary goal was to achieve uniform wireless power delivery throughout the mazes through a comparative study of different transmitter (Tx) array configurations, such as float, series, and parallel resonators. The calculated Specific Absorption Rate (SAR) in rat tissue model equals 1.7 W/kg at the power carrier frequency of 13.56 MHz. A prototype of the proposed maze-based WPT design, featuring 8 Tx resonators, a Tx coil and power amplifier, and a headstage power harvesting unit, is successfully implemented and its performance characterized for all three resonator configurations. The implemented T maze-based WPT system has a total length of 128 cm. In the overlapping Tx resonators configuration, a homogeneity of 94% is achieved for the measured power transfer efficiency at over 30%, while continuously delivering over 60 mW for series configuration.

This paper presents a novel resonance-based, adaptable, and flexible inductive wireless power transmission (WPT) link for powering implantable and wearable devices throughout the human body. The proposed design provides a comprehensive solution for wirelessly delivering power, sub-micro to hundreds of milliwatts, to deep-tissue implantable devices (3D space of human body) and surface-level wearable devices (2D surface of human skin) safely and seamlessly. The link comprises a belt-fitted transmitter (Belt-Tx) coil equipped with a power amplifier (PA) and a data demodulator unit, two resonator clusters (to cover upper-body and lower-body), and a receiver (Rx) unit that consists of Rx load and resonator coils, rectifier, microcontroller, and data modulator units for implementing a closed-loop power control (CLPC) mechanism. All coils are tuned at 13.56 MHz, Federal Communications Commission (FCC)-approved industrial, scientific, and medical (ISM) band. Novel customizable configurations of resonators in the clusters, parallel for implantable devices and cross-parallel for wearable devices and vertically oriented implants, ensure uniform power delivered to the load, PDL, enabling natural Tx power localization toward the Rx unit. The proposed design is modeled, simulated, and optimized using ANSYS HFSS software. The Specific Absorption Rate (SAR) is calculated under 1.5 W/kg, indicating the design’s safety for the human body. The proposed link is implemented, and its performance is characterized. For both the parallel cluster (implant) and cross-parallel cluster (wearable) scenarios, the measured results indicate: 1) an upper-body PDL exceeding 350 mW with a Power Transfer Efficiency (PTE) reaching 25%, and 2) a lower-body PDL surpassing 360 mW with a PTE of up to 20%, while covering up to 92% of the human body.

This paper presents a highly scalable and rack-mountable wireless sensing system for long-term monitoring (i.e., sense and estimate) of small animal/s' physical state (SAPS), such as changes in location and posture within standard cages. The conventional tracking systems may lack one or more features such as scalability, cost efficiency, rack-mount ability, and light condition insensitivity to work 24/7 on a large scale. The proposed sensing mechanism relies on relative changes of multiple resonance frequencies due to the animal's presence over the sensor unit. The sensor unit can track SAPS changes based on changes in electrical properties in the sensors near fields, appearing in the resonance frequencies, i.e., an Electromagnetic (EM) Signature, within the 200 MHz - 300 MHz frequency range. The sensing unit is located underneath a standard mouse cage and consists of thin layers of a reading coil and six resonators tuned at six distinct frequencies. ANSYS HFSS software is used to model and optimize the proposed sensor unit and calculate the Specific Absorption Rate (SAR) obtained under 0.05 W/kg. Multiple prototypes have been implemented to test, validate, and characterize the performance of the design by conducting in vitro and in vivo experiments on Mice. The in-vitro test results have shown a 15 mm spatial resolution in detecting the mouse's location over the sensor array having maximum frequency shifts of 832 kHz and posture detection with under 30º resolution. The in-vivo experiment on mouse displacement resulted in frequency shifts of up to 790 kHz, indicating the SAPS's capability to detect the Mice's physical state.

This paper presents an automatic camera-based device to monitor and evaluate the gait speed, standing balance, and 5 Times Sit-Stand (5TSS) tests of the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG) test. The proposed design measures and calculates the parameters of the SPPB tests automatically. The SPPB data can be used for physical performance assessment of older patients under cancer treatment. This stand-alone device has a Raspberry Pi (RPi) computer, three cameras, and two DC motors. The left and right cameras are used for gait speed tests. The center camera is used for standing balance, 5TSS, and TUG tests and for angle positioning of the camera platform toward the subject using DC motors by turning the camera left/right and tilting it up/down. The key algorithm for operating the proposed system is developed using Channel and Spatial Reliability Tracking in the cv2 module in Python. Graphical User Interfaces (GUIs) in the RPi are developed to run tests and adjust cameras, controlled remotely via smartphone and its Wi-Fi hotspot. We have tested the implemented camera setup prototype and extracted all SPPB and TUG parameters by conducting several experiments on a human subject population of 8 volunteers (male and female, light and dark complexions) in 69 test runs. The measured data and calculated outputs of the system consist of tests of gait speed (0.041 to 1.92 m/s with average accuracy of >95%), and standing balance, 5TSS, TUG, all with average time accuracy of >97%.