Since its first introduction, levodopa has remained the cornerstone treatment for Parkinson’s disease. However, as the disease advances, the therapeutic window for levodopa narrows, leading to motor complications like fluctuations and dyskinesias. Clinicians face challenges in optimizing daily therapeutic regimens, particularly in advanced stages, due to the lack of quantitative biomarkers for continuous motor monitoring. Biochemical sensing of levodopa offers a promising approach for real-time therapeutic feedback, potentially sustaining an optimal motor state throughout the day. These sensors vary in invasiveness, encompassing techniques like microdialysis, electrochemical non-enzymatic sensing, and enzymatic approaches. Electrochemical sensing, including wearable solutions that utilize reverse iontophoresis and microneedles, is notable for its potential in non-invasive or minimally invasive monitoring. Point-of-care devices and standard electrochemical cells demonstrate superior performance compared to wearable solutions; however, this comes at the cost of wearability. As a result, they are better suited for clinical use. The integration of nanomaterials such as carbon nanotubes, metal–organic frameworks, and graphene has significantly enhanced sensor sensitivity, selectivity, and detection performance. This framework paves the way for accurate, continuous monitoring of levodopa and its metabolites in biofluids such as sweat and interstitial fluid, aiding real-time motor performance assessment in Parkinson’s disease. This review highlights recent advancements in biochemical sensing for levodopa and catecholamine monitoring, exploring emerging technologies and their potential role in developing closed-loop therapy for Parkinson’s disease.

Quality control is mandatory in the food industry and chemical sensors play a crucial role in this field. Coffee is one of the most consumed and commercialized food products globally, and its quality is of the utmost importance. Many scientific papers have analyzed coffee quality using different approaches, such as analytical and sensor analyses, which, despite their good performance, are limited to structured lab implementation. This study aims to evaluate the capability of a smart electrochemical sensor to discriminate among different beverages prepared using coffee beans with different moisture content (0%, 2%, >4%) and ground in three sizes (fine, medium and coarse). These parameters reflect real scenarios where coffee is produced and its quality influenced. The possibility of optimizing coffee quality in real time by tuning these parameters could open the way to intelligent coffee machines. A specific experimental setup has been designed, and the data has been analyzed using machine learning techniques. The results obtained from Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) show the sensor’s capability to distinguish between samples of different quality, with a percentage of correct classification of 86.6%. This performance underscores the potential benefits of this sensor for coffee quality assessment, enabling time and resource savings, while facilitating the development of analytical methods based on smart electrochemical sensors.

In this paper, we present a novel impedance measurement circuit with a wideband coverage up to 1 MHz. A frequency divider technique is applied to downshift the input frequency of the XOR input and at the same time adding 90° phase shift. This technique helps to avoid the typically dead-zone problem in XOR-based phase detectors still mantaining 10 mV/deg of phase sensitivity. The proposed circuit implement the polar demodulation structure with a reference path providing reference timing mitigating synchronization issues with the transmitter. To counteract both the delay in the comparator and the instrumentation amplifier (IA) non-linear characteristics, a reference magnitude measurement pathway has been incorporated into the design. This architectural enhancement ensures that measurement precision is primarily constrained by component matching variations within the circuit itself. The sampling scheme includes a current controlled impedance analysis that includes a dynamic inverting opamp configuration in order to mantain the ratio comparable to the reference signal. The circuit while covering the measurement frequency range from 10 Hz to 1 MHz and exhibiting a maximum modulus and phase errors of 11% and 0.51°, respectively.

Electrical stimulation can be used in several applications such as fatigue reduction, muscle rehabilitation, neurorehabilitation, neuro-prosthesis and pain relief. Moreover, electrical stimulation can be used for drug delivery applications or body fluids extraction (e.g., sweat and interstitial fluid) to successively monitor several parameters, such as glucose, lactate, etc. All these applications are performed using electrical stimulator devices capable of applying constant voltage pulses or constant current pulses via electrodes to human tissues. Usually, constant current stimulators are most widely used because of their safety, stability, and repeatability. Thus, the aim of this work was to design, realize and test a mixed-signal electronic interface capable of producing current pulses with custom amplitude, duration, frequency, polarity and symmetry with extended voltage compliance. To achieve this result, we developed a high-voltage current stimulator suitable for iontophoresis applications. Current stimuli can be applied setting the intensity, frequency and duty cycle of the stimulation patterns through a µC. A custom electronic interface was designed to allow the control of the injected current in real time and to prevent electrical injuries to the patient by avoiding potential unwanted short circuits. Moreover, the system was tested in a simulated environment demonstrating its effectiveness and applicability for transdermal monitoring applications. The obtained results show that the device is able to apply monophasic and biphasic pulses, ranging from 0.1 to 10 mA, with a maximum error of about 10% at the minimum intensity; in addition, current stimuli can be applied up to a maximum frequency of 100 kHz with a voltage compliance of 120 V.

Diabetes mellitus represents one of the most widespread chronic diseases globally, characterized by alterations in glucose metabolism that require constant monitoring of blood glucose levels. Traditionally, blood testing has been the standard for glucose monitoring; however, interstitial fluid has emerged as a viable alternative, due to its less invasive nature which enhances user comfort. Despite improvements in technology, the accuracy of currently available continuous glucose monitors remains a concern, particularly when the rate of change is higher, such as in hypoglycemic and hyperglycemic ranges. Effective management of hypoglycemia relies on the monitor’s ability to provide precise and specific readings when blood glucose levels drop dangerously low. In this context, the demand for heightened accuracy is paramount to timely alert users to impending hypoglycemic events. The inaccuracies of these sensors are attributed to the dynamics of the sample analysis. Specifically the interstitial fluid experiences a delay in concentration due to the diffusion process from capillary blood to interstitial fluid. In this study, we developed a microfluidic device that simulates the diffusion dynamics from capillary glucose to interstitial fluid. We demonstrate the reduction of lag time diffusion from 20 min to 5 min by increasing dermal electro-osmotic flow, which generates convection that transports glucose faster than diffusion, thus resulting in lower lag times. These findings highlight the potential of inciting electro-osmotic flow for improving the responsiveness and accuracy of CGMs, ultimately enhancing diabetes management for users.