Bioimpedance Sensor and Methodology for Acute Pain Monitoring

Abstract

The paper aims to revive the interest in bioimpedance analysis for pain studies in communicating and non-communicating (anesthetized) individuals for monitoring purpose. The plea for exploitation of full potential offered by the complex (bio)impedance measurement is emphasized through theoretical and experimental analysis. A non-invasive, low-cost reliable sensor to measure skin impedance is designed with off-the-shelf components. This is a second generation prototype for pain detection, quantification, and modeling, with the objective to be used in fully anesthetized patients undergoing surgery. The 2D and 3D time–frequency, multi-frequency evaluation of impedance data is based on broadly available signal processing tools. Furthermore, fractional-order impedance models are implied to provide an indication of change in tissue dynamics correlated with absence/presence of nociceptor stimulation. The unique features of the proposed sensor enhancements are described and illustrated here based on mechanical and thermal tests and further reinforced with previous studies from our first generation prototype.

Perspectives on Hybrid Control of the Anesthesia-Hemodynamic System in the Pandemic Context

“…Currently, closed-loop strategies can be classified as single input single output (SISO), multiple inputs single output (MISO) or multiple inputs multiple outputs (MIMO). SISO systems have been thoroughly investigated for hypnosis and NMB, whereas specifically controlled analgesia is just recently emerging due to the new pain monitors evaluated in research [26], [27], [28]. Measurement of analgesia is still constrained, as [29] obtained an inconclusive review about the nociception monitoring effect on anesthesia optimization, caused by the lack of homogeneous trials for a systematic comparison of pain devices.…”

Feasibility of intelligent drug control in the maintenance phase of general anesthesia based on convolutional neural network

“…In the research direction of anesthesia modeling and control, Visioli and coworkers used a proportional-integral-derivative controller to regulate the depth of hypnosis in anesthesia by using propofol administration and bispectral index as control variables [ 21 ]. Ionescu and colleagues described a bioimpedance sensor's development and validation for time-frequency analysis of pain phenomena [ 22 ]. They later proposed a mathematical framework for drug capture estimation in PK models for estimating optimal drug infusion rates to maintain long-term anesthesia in Covid-19 patients [ 23 ].…”

Improved Individualized Patient-Oriented Depth-of-Hypnosis Measurement Based on Bispectral Index

“…In the field of drug delivery systems, this includes modeling, control, analysis, and pharmacological studies, as well as development of novel medical devices and conducting of targeted clinical trials. In this regard, the systematic employment of dynamic-system analysis along with control theory offers a wide range of application opportunities in the medical domain [ 15 , 16 , 17 , 18 , 19 , 20 ]. Despite the fact that for TCI various PK models can be implemented, all having their own advantages and drawbacks, the Marsh [ 21 ] and Schnieder [ 22 , 23 ] models are mainly used in clinical practice.…”

“…Furthermore, they represent the basis for a number of advanced control approaches, such asrobust control [ 32 , 33 , 34 ], model-predictive control [ 35 , 36 ], fuzzy-rule-based decision system [ 37 ], event-based control [ 38 ], etc. Despite difficulties in objective pain measurement [ 18 , 39 ], a number of articles also consider the inherent MIMO (or MISO) nature of the controlled system, which is due to drug interactions, especially when analgesics (such as remeifentanil) are considered [ 40 , 41 , 42 ].…”