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Objective:To determine the validity of the key mathematical assumptions used in electrical impedance tomography for human head tissues.Approach:Conductivity and permittivity data collected from available literature for each tissue within the human head have been evaluated and critiqued. The most relevant dielectric tissue data for each tissue was then used to assess the validity of the mathematical assumptions of electrical impedance tomography in terms of their suitability for human head imaging in order to estimate related errors.Main Results:For induced currents with frequencies greater than 200 Hz the internal current source density is negligible. The assumption that magnetic effects are negligible is valid to an error of 1.7% for human head tissues for frequencies below 1 MHz. The capacitive effects are negligible for CSF, dura mater, blood, bone (cortical), and deep tissue skin for frequencies less than 3.2 MHz, 320 kHz, 25 kHz, 3.2 kHz, and 130 Hz respectively. However, the capacitive effects are not negligible for brain tissues, as the minimum error for brain tissues across the frequency range of 10 Hz to 100 GHz is 6.2% at 800 Hz, and the maximum error is 410% at 20 GHz.Significance:It is often assumed that the mathematical reduction of the base equations is valid for human head tissues over a broad frequency range; this study shows that these assumptions are not true for all tissues at all frequencies. False assumptions will result in greater errors and local distortions within tomographic images of the human head using electrical impedance tomography. This study provides the relationships between injected current frequency and the validity of the mathematical assumptions for each individual tissue, providing greater awareness of the magnitude of possible distortions.

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High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for individuals with a speech disability, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain-computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user's environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

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Augmentative and alternative communication (AAC) systems tend to rely on the interpretation of purposeful gestures for interaction. Existing AAC methods could be cumbersome and limit the solutions in terms of versatility. The study aims to interpret breathing patterns (BPs) to converse with the outside world by means of a unidirectional microphone and researches breathing-pattern interpretation (BPI) to encode messages in an interactive manner with minimal training. We present BP processing work with (1) output synthesized machine-spoken words (SMSW) along with single-channel Weiner filtering (WF) for signal de-noising, and (2) k-nearest neighbor (k-NN) classification of BPs associated with embedded dynamic time warping (DTW). An approved protocol to collect analogue modulated BP sets belonging to 4 distinct classes with 10 training BPs per class and 5 live BPs per class was implemented with 23 healthy subjects. An 86% accuracy of k-NN classification was obtained with decreasing error rates of 17%, 14%, and 11% for the live classifications of classes 2, 3, and 4, respectively. The results express a systematic reliability of 89% with increased familiarity. The outcomes from the current AAC setup recommend a durable engineering solution directly beneficial to the sufferers.

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PURPOSE: Bone drilling is a major part of orthopaedic surgery performed during the internal fixation of fractured bones. At present, information related to drilling force, drilling torque, rate of drill-bit penetration and drill-bit rotational speed is not available to orthopaedic surgeons, clinicians and researchers as bone drilling is performed manually. METHODS: This study demonstrates that bone drilling force data if recorded in-vivo, during the repair of bone fractures, can provide information about the quality of the bone. To understand the variability and anisotropic behaviour of cortical bone tissue, specimens cut from three anatomic positions of pig and bovine were investigated at the same drilling speed and feed rate. RESULTS: The experimental results showed that the drilling force does not only vary from one animal bone to another, but also vary within the same bone due to its changing microstructure. Drilling force does not give a direct indication of bone quality; therefore it has been correlated with screw pull-out force to provide a realistic estimation of the bone quality. A significantly high value of correlation (r2 = 0.93 for pig bones and r2 = 0.88 for bovine bones) between maximum drilling force and normalised screw pull-out strength was found. CONCLUSIONS: The results show that drilling data can be used to indicate bone quality during orthopaedic surgery.

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BACKGROUND: In certain medical applications, it is necessary to be able to determine the position of a needle inside the body, specifically with regards to identifying certain tissue types. By measuring the electrical impedance of specific tissue types, it is possible to determine the type of tissue the tip of the needle (or probe) is at. MATERIALS AND METHODS: Two methods have been investigated for electric impedance detection; bipolar and monopolar. Commercially available needle electrodes are of a monopolar type. Although many patents exist on the bipolar setups, these have not as yet been commercialized. This paper reports a comparison of monopolar and bipolar setups for tissue type determination. In vitro experiments were carried out on pork to compare this investigation with other investigations in this field. RESULTS: The results show that both monopolar and bipolar setups are capable of determining tissue type. However, the bipolar setup showed slightly better results; the difference between the different soft tissue type impedances was greater compared to the monopolar method. CONCLUSION: Both monopolar and bipolar electrical impedance setups work very similarly in inhomogeneous volumes such as biological tissue. There is a clear potential for clinical applications with impedance-based needle guidance, with both the monopolar and bipolar setups. It is, however, worth noting that the bipolar setup is more versatile.

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Bone drilling is an essential part of many orthopaedic surgery procedures, including those for internal fixation and for attaching prosthetics. Estimation and control of bone drilling forces are critical to prevent drill-bit breakthrough, excessive heat generation, and mechanical damage to the bone. An experimental and computational study of drilling in cortical bone has been conducted. A 3D finite element (FE) model for prediction of thrust forces experienced during bone drilling has been developed. The model incorporates the dynamic characteristics involved in the process along with geometrical considerations. An elastic-plastic material model is used to predict the behaviour of cortical bone during drilling. The average critical thrust forces and torques obtained using FE analysis are found to be in good agreement with the experimental results.

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Electrical Impedance Tomography is a non-invasive and portable method that has good potential as an alternative to the conventional modalities for early detection of intracranial haematomas in high risk patients. Early diagnosis can reduce treatment delays and most significantly can impact patient outcomes. Two eight-electrode layouts, a standard ring full array (FA) and a semi-array (SA), were investigated for their ability to detect, localise and quantify simulated intracranial haematomas in vitro on ovine models for the purpose of early diagnosis. SA layout speeds up electrode application and avoids the need to move and lift the patient's head. Haematomas were simulated using gel samples with the same conductivity as blood. Both layouts, FA and SA, could detect the presence of haematomas at any location within the skull. The mean of the relative radial position error with respect to the brain radius was 7% for FA and 6% for SA, for haematomas close to the electrodes, and 11% for SA for haematomas far from the electrodes at the back of the head. Size estimation was not as good; the worst size estimation error for FA being around 30% while the best for SA was 50% for simulated haematomas close to the electrodes.

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