A small-size microwave sensor is developed for non-contact imaging of a human body structure in 2D, enabling fitness and health monitoring using mobile devices. A method for human body tissue structure imaging is developed and experimentally validated. Subcutaneous fat tissue reconstruction depth of up to 70 mm and maximum fat thickness measurement error below 2 mm are demonstrated by measurements with a human body phantom and human subjects. Electrically small antennas are developed for integration of the microwave sensor into a mobile device. Usability of the developed microwave sensor for fitness applications, healthcare, and body weight management is demonstrated.

In this Letter, a robust third-order tensor decomposition of multi-lead electrocardiogram (MECG) comprising of 12-leads is proposed to reduce the dimension of the storage data. An order-3 tensor structure is employed to represent the MECG data by rearranging the MECG information in three dimensions. The three-dimensions of the formed tensor represent the number of leads, beats and samples of some fixed ECG duration. Dimension reduction of such an arrangement exploits correlations present among the successive beats (intra-beat and inter-beat) and across the leads (inter-lead). The higher-order singular value decomposition is used to decompose the tensor data. In addition, multiscale analysis has been added for effective care of ECG information. It grossly segments the ECG characteristic waves (P-wave, QRS-complex, ST-segment and T-wave etc.) into different sub-bands. In the meantime, it separates high-frequency noise components into lower-order sub-bands which helps in removing noise from the original data. For evaluation purposes, we have used the publicly available PTB diagnostic database. The proposed method outperforms the existing algorithms where compression ratio is under 10 for MECG data. Results show that the original MECG data volume can be reduced by more than 45 times with acceptable diagnostic distortion level.

In this Letter the authors explore the communication capabilities of optical wireless technology for a wearable device dedicated to healthcare application. In an indoor environment sensible to electromagnetic perturbations such as a hospital, the use of optical wireless links can permit reducing the amount of radio frequencies in the patient environment. Moreover, this technology presents the advantage to be secure, low-cost and easy to deploy. On the basis of commercially available components, a custom-made wearable device is presented, which allows optical wireless transmission of accelerometer data in the context of physical activity supervision of post-stroke patients in hospital. Considering patient mobility, the experimental performance is established in terms of packet loss as a function of the number of receivers fixed to the ceiling. The results permit to conclude that optical wireless links can be used to perform such mobile remote monitoring applications. Moreover, based on the measurements obtained with one receiver, it is possible to theoretically determine the performance according to the number of receivers to be deployed.

To establish the optimal radiotherapy fields for treating brain cancer patients, the tumour volume is often outlined on magnetic resonance (MR) images, where the tumour is clearly visible, and mapped onto computerised tomography images used for radiotherapy planning. This process requires considerable clinical experience and is time consuming, which will continue to increase as more complex image sequences are used in this process. Here, the potential of image analysis techniques for automatically identifying the radiation target volume on MR images, and thereby assisting clinicians with this difficult task, was investigated. A gradient-based level set approach was applied on the MR images of five patients with grades II, III and IV malignant cerebral glioma. The relationship between the target volumes produced by image analysis and those produced by a radiation oncologist was also investigated. The contours produced by image analysis were compared with the contours produced by an oncologist and used for treatment. In 93% of cases, the Dice similarity coefficient was found to be between 60 and 80%. This feasibility study demonstrates that image analysis has the potential for automatic outlining in the management of brain cancer patients, however, more testing and validation on a much larger patient cohort is required.

Functional electric stimulators that produce near-ideal, charge-balanced biphasic stimulation waveforms with interphase delay are considered safer and more efficacious than conventional stimulators. An indigenously designed, low-cost, portable FES device named InStim is developed. It features a charge-balanced biphasic single channel. The authors present the complete design, mathematical analysis of the circuit and the clinical evaluation of the device. The developed circuit was tested on stroke patients affected by foot drop problems. It was tested both under laboratory conditions and in clinical settings. The key building blocks of this circuit are low dropout regulators, a DC–DC voltage booster and a single high-power current source OP-Amp with current-limiting capabilities. This allows the device to deliver high-voltage, constant current, biphasic pulses without the use of a bulky step-up transformer. The advantages of the proposed design over the currently existing devices include improved safety features (zero DC current, current-limiting mechanism and safe pulses), waveform morphology that causes less muscle fatigue, cost-effectiveness and compact power-efficient circuit design with minimal components. The device is also capable of producing appropriate ankle dorsiflexion in patients having foot drop problems of various Medical Research Council scale grades.