Parkinson's Disease (PD) is a neurodegenerative disorder that manifests as an impairment of motor and non-motor abilities due to a loss of dopamine input to deep brain structures. While there is presently no cure for PD, a variety of pharmacological and surgical therapeutic interventions have been developed to manage PD symptoms. This review explores the past, present and future outlooks of PD treatment, with particular attention paid to deep brain stimulation (DBS), the surgical procedure to deliver DBS, and its limitations. Finally, our group's efforts with respect to brain mapping for DBS targeting will be discussed.

To perform activities of daily living (ADL), people with lower limb amputation depend on the prosthetic socket for stability and proprioceptive feedback. Poorly fitting sockets can cause discomfort, pain, limb tissue injuries, limited device usage, and potential rejection. Semi-passively controlled adjustable socket technologies exist, but these depend upon the user's perception to determine safe interfacial pressure levels. This paper presents a framework for automatic control of an adjustable transtibial prosthetic socket that enables active adaptation of residuum-socket interfacial loading through localized actuators, based on soft tissue injury risk estimation. Using finite element analysis, local interfacial pressure vs. compressive tissue strain relationships were estimated for three discrete anatomical actuator locations, for tissue injury risk assessment within a control structure. Generalized Predictive Control of multiple actuators was implemented to maintain interfacial pressure within estimated safe and functional limits. Controller simulation predicted satisfactory dynamic performance in several scenarios. Actuation rates of 0.06-1.51kPa/s with 0.67% maximum overshoot, and 0.75-1.58kPa/s were estimated for continuous walking, and for a demonstrative loading sequence of ADL, respectively. The developed platform could be useful for extending recent efforts in adjustable lower limb prosthetic socket design, particularly for individuals with residuum sensory impairment.

Humans have suffered from a variety of infectious diseases since a long time ago, and now a new infectious disease called COVID-19 is prevalent worldwide. The ongoing COVID-19 pandemic has led to research of the effective methods of diagnosing respiratory infectious diseases, which are important to reduce infection rate and help the spread of diseases be controlled. The onset of COVID-19 has led to the further development of existing diagnostic methods such as polymerase chain reaction, reverse transcription polymerase chain reaction, and loop-mediated isothermal amplification. Furthermore, this has contributed to the further development of micro/nanotechnology-based diagnostic methods, which have advantages of high-throughput testing, effectiveness in terms of cost and space, and portability compared to conventional diagnosis methods. Micro/nanotechnology-based diagnostic methods can be largely classified into (1) nanomaterials-based, (2) micromaterials-based, and (3) micro/nanodevice-based. This review paper describes how micro/nanotechnologies have been exploited to diagnose respiratory infectious diseases in each section. The research and development of micro/nanotechnology-based diagnostics should be further explored and advanced as new infectious diseases continue to emerge. Only a handful of micro/nanotechnology-based diagnostic methods has been commercialized so far and there still are opportunities to explore.

Rapid and sensitive detection of pathogenic bacteria in various samples, including food and drinking water, is important to prevent bacterial diseases. Most bacterial solutions contain only a small number of bacteria in complex matrices with impurities; hence, pretreatment is necessary to separate and concentrate target bacteria before sensing. Among various pretreatment methods, iron oxide magnetic nanoparticle (MNP)-based pretreatment has drawn attention owing to the unique properties of MNP, such as high magnetic susceptibility, superparamagnetism, and biocompatibility. After target bacteria are captured by recognition molecule-functionalized MNPs, bacteria–MNP complexes can be easily separated and enriched by applying an external magnetic field. Various devices, such as optical, electrochemical, and magnetoresistance sensors, can be used to detect target bacteria, and their detection principles have been discussed in numerous review papers. Herein, we focus on recent research advances and challenges in magnetic pretreatment of pathogenic bacteria using microfluidic devices, which offer the advantages of process automation and miniaturization.

In the last decade, an emerging three-dimensional (3D) printing technique named freeform 3D printing has revolutionized the biomedical engineering field by allowing soft matters with or without cells to be printed and solidified with high precision regardless of their poor self-supportability. The key to this freeform 3D printing technology is the supporting matrices that hold the printed soft ink materials during omnidirectional writing and solidification. This approach not only overcomes structural design restrictions of conventional layer-by-layer printing but also helps to realize 3D printing of low-viscosity or slow-curing materials. This article focuses on the recent developments in freeform 3D printing of soft matters such as hydrogels, cells, and silicone elastomers, for biomedical engineering. Herein, we classify the reported freeform 3D printing systems into positive, negative, and functional based on the fabrication process, and discuss the rheological requirements of the supporting matrix in accordance with the rheological behavior of counterpart inks, aiming to guide development and evaluation of new freeform printing systems. We also provide a brief overview of various material systems used as supporting matrices for freeform 3D printing systems and explore the potential applications of freeform 3D printing systems in different areas of biomedical engineering.

In the anesthesia automation, an automatic propofol infusion system uses Bi-spectral Index Signal (BIS) as a primary feedback signal to manipulate propofol dose. However, the BIS signal may be suspended for some time due to poor EEG signal quality, noise, and many other factors. Therefore, BIS signal failure may be the main cause of inadequate propofol infusion. This fact motivates the need for integration of multivariable fault tolerance module (MFTM) and fractional-order Smith predictor controller to avoid adverse reactions of inadequate propofol dosing during BIS failure. Smith Predictor control strategy is sufficiently robust to predict feedback BIS during BIS failure via patient pharmacological modeled BIS. However, modeled BIS may not provide a guarantee of adequate propofol infusion during BIS failure and especially in the presence of hypotension and hypertension. Thus, the proposed control strategy is designed with MFTM to detect BIS sensor fault and to estimate feedback BIS during BIS failure. Further, the proposed control strategy is designed with a multivariable pharmacological patient model to analyze the cross effect of propofol infusion on BIS and hemodynamic variables. The robustness of the proposed control strategy is tested in the presence of noxious surgical stimulation, BIS sensor fault and heavy hemodynamic disturbance. The pharmacological parameters and recorded signals of 30 patients during various surgeries have been used to validate simulated results. The performance of the proposed control strategy assures optimization and smooth propofol infusion during BIS failure. The proposed system provides stability for a wide range of physiological parameters range. The proposed scheme maintains smooth BIS and MAP signal despite the delay, BIS sensor fault, and surgical disturbances.

Osseointegrated (OI) prosthetic limbs have been shown to provide an advantageous treatment option for amputees. In order for the OI prosthesis to be successful, the titanium implant must rapidly achieve and maintain proper integration with the bone tissue and remain free of infection. Electrochemical methods can be utilized to control and/or monitor the interfacial microenvironment where the titanium implant interacts with the biological system (host bone tissue or bacteria). This review will summarize the current understanding of how electrochemical modalities can influence bone tissue and bacteria with specific emphasis on applications where the metallic prosthesis itself can be utilized directly as a stimulating electrode for enhanced osseointegration and infection control. In addition, a summary of electrochemical impedance sensing techniques that could be used to potentially assess osseointegration and infection status of the metallic prosthesis is presented.

The socket is the most critical part of every lower-limb prosthetic system, since it serves as the interfacial component that connects the residual limb with the artificial system. However, many amputees abandon their socket prostheses due to the high-level of discomfort caused by the poor interaction between the socket and residual limb. In general, socket prosthesis performance is determined by three main factors, namely, residual limb-socket interfacial stress, volume fluctuation of the residual limb, and temperature. This review paper summarizes the various sensing and actuation solutions that have been proposed for improving socket performance and for realizing next-generation socket prostheses. The working principles of different sensors and how they have been tested or used for monitoring the socket interface are discussed. Furthermore, various actuation methods that have been proposed for actively modifying and improving the socket interface are also reviewed. Through the continued development and integration of these sensing and actuation technologies, the long-term vision is to realize smart socket prostheses. Such smart socket systems will not only function as a socket prosthesis but will also be able to sense parameters that cause amputee discomfort and self-adjust to optimize its fit, function, and performance.

Osseointegration (OI) is the direct attachment of bone onto a titanium implant. Recently, the term is used to describe "transdermal" implants that allow an external prosthesis to be connected directly to the skeleton. This technology eliminates the challenges of conventional socket-based prostheses, such as skin breakdown and poor fit, which are common in patients with major extremity amputations. Osseointegration patients demonstrate encouraging improvements in quality of life and function. Patients report improvement in prosthetic use, prosthetic mobility, global health, and pain reduction on a variety of clinical assessment tools. Various implants have been developed for osseointegration for amputees. These implants use a variety of fixation strategies and surface augments to allow for successful integration into the host bone. Regardless of design, all OI implants face similar challenges, particularly infections. Other challenges include the inability to determine when integration has occurred and the inability to detect loss of integration. These challenges may be met by incorporating sensing systems into the implants. The percutaneous nature of the metal devices can be leveraged so that internal sensors need not be wireless, and can be interrogated by external monitoring systems, thus providing crucial, real-time information about the state of the implant. The purpose of this review is to (1) review the basic science behind osseointegration, (2) provide an overview of current implants, practice patterns, and clinical outcomes, and (3) preview sensor technologies which may prove useful in future generations of transdermal orthopaedic implants.