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Heterodyne mixing of millimetre electromagnetic waves and sub-THz sound in a semiconductor device.

ABSTRACT: We demonstrate heterodyne mixing of a 94?GHz millimetre wave photonic signal, supplied by a Gunn diode oscillator, with coherent acoustic waves of frequency ~100?GHz, generated by pulsed laser excitation of a semiconductor surface. The mixing takes place in a millimetre wave Schottky diode, and the intermediate frequency electrical signal is in the 1-12?GHz range. The mixing process preserves all the spectral content in the acoustic signal that falls within the intermediate frequency bandwidth. Therefore this technique may find application in high-frequency acoustic spectroscopy measurements, exploiting the nanometre wavelength of sub-THz sound. The result also points the way to exploiting acoustoelectric effects in photonic devices working at sub-THz and THz frequencies, which could provide functionalities at these frequencies, e.g. acoustic wave filtering, that are currently in widespread use at lower (GHz) frequencies.

SUBMITTER: Heywood SL

PROVIDER: S-EPMC4967867 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Heterodyne mixing of millimetre electromagnetic waves and sub-THz sound in a semiconductor device.

Heywood Sarah L SL Glavin Boris A BA Beardsley Ryan P RP Akimov Andrey V AV Carr Michael W MW Norman James J Norton Philip C PC Prime Brian B Priestley Nigel N Kent Anthony J AJ

Scientific reports 20160801

We demonstrate heterodyne mixing of a 94 GHz millimetre wave photonic signal, supplied by a Gunn diode oscillator, with coherent acoustic waves of frequency ~100 GHz, generated by pulsed laser excitation of a semiconductor surface. The mixing takes place in a millimetre wave Schottky diode, and the intermediate frequency electrical signal is in the 1-12 GHz range. The mixing process preserves all the spectral content in the acoustic signal that falls within the intermediate frequency bandwidth. ...[more]

PMID: 27477841

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Project description:Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient's middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients.

Dataset Information

Heterodyne mixing of millimetre electromagnetic waves and sub-THz sound in a semiconductor device.

Publications

Heterodyne mixing of millimetre electromagnetic waves and sub-THz sound in a semiconductor device.

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