Noncontact optical sensor for bone fracture diagnostics

Non-contact optical in-vivo sensing of cilia motion by analyzing speckle patterns

Cilia motion is an indicator of pathological-ciliary function, however current diagnosis relies on biopsies. In this paper, we propose an innovative approach for sensing cilia motility. We present an endoscopic configuration for measuring the motion frequency of cilia in the nasal cavity. The technique is based on temporal tracking of the reflected spatial distribution of defocused speckle patterns while illuminating the cilia with a laser. The setup splits the optical signal into two channels; One imaging channel is for the visualization of the physician and another is, defocusing channel, to capture the speckles. We present in-vivo measurements from healthy subjects undergoing endoscopic examination. We found an average motion frequency of around 7.3 Hz and 9.8 Hz in the antero-posterior nasal mucus (an area rich in cilia), which matches the normal cilia range of 7–16 Hz. Quantitative and precise measurements of cilia vibration will optimize the diagnosis and treatment of pathological-ciliary function. This method is simple, minimally invasive, inexpensive, and promising to distinguish between normal and ciliary dysfunction.

Implants with Sensing Capabilities

Because of the aging human population and increased numbers of surgical procedures being performed, there is a growing number of biomedical devices being implanted each year. Although the benefits of implants are significant, there are risks to having foreign materials in the body that may lead to complications that may remain undetectable until a time at which the damage done becomes irreversible. To address this challenge, advances in implantable sensors may enable early detection of even minor changes in the implants or the surrounding tissues and provide early cues for intervention. Therefore, integrating sensors with implants will enable real-time monitoring and lead to improvements in implant function. Sensor integration has been mostly applied to cardiovascular, neural, and orthopedic implants, and advances in combined implant-sensor devices have been significant, yet there are needs still to be addressed. Sensor-integrating implants are still in their infancy; however, some have already made it to the clinic. With an interdisciplinary approach, these sensor-integrating devices will become more efficient, providing clear paths to clinical translation in the future.

On the Design and Development of Planar Monopole Antenna for Bone Crack/Void Detection

In this study, the design of a compact narrowband monopole antenna for bone crack detection is presented. The proposed antenna consists of a modified hexagon-shaped radiator with six triangular slits integrated on its bottom periphery, a rectangular-shaped ground plane, and a microstrip feed line of 50 Ω. The antenna is fabricated on the FR-4 substrate with a thickness of 1.6 mm, an overall size of 32 mm × 30 mm, and electrical dimensions of 0.13λ0 × 0.122λ0, where λ0 is the free space wavelength at 2.45 GHz. The resonant frequency of the designed antenna is 2.45 GHz. The antenna offers a gain of 1.68 dB and an efficiency of 85.3%. The presence of a crack in the bone is detected by observing the shift in the peak resonating frequency of the antenna. This method can detect bone fractures in a noninvasive manner. The human arm model is constructed, and the effect of bone cracks of different lengths on the resonating frequency is investigated. The pig bone and tissues are used to validate the simulated results. The simulated results are in agreement with the measured outcomes. Also, the specific absorption rate (SAR) of the antenna is calculated and found to be less than 0.57 W/kg. The designed monopole antenna has several advantages, including a small footprint, straightforward design, low cost, and easy integration with other devices. The proposed method is suitable for primary-level bone crack diagnosis.

Remote photonic detection of human senses using secondary speckle patterns

Neural activity research has recently gained significant attention due to its association with sensory information and behavior control. However, the current methods of brain activity sensing require expensive equipment and physical contact with the tested subject. We propose a novel photonic-based method for remote detection of human senses. Physiological processes associated with hemodynamic activity due to activation of the cerebral cortex affected by different senses have been detected by remote monitoring of nano-vibrations generated by the transient blood flow to the specific regions of the human brain. We have found that a combination of defocused, self-interference random speckle patterns with a spatiotemporal analysis, using Deep Neural Network, allows associating between the activated sense and the seemingly random speckle patterns.

Non-contact optical sensing of vocal fold vibrations by secondary speckle patterns

Vocal folds lesions are commonly diagnosed using an endoscopic-stroboscope. However, the stroboscopic picture of the vocal folds vibrations is subjectively and qualitatively evaluated by the clinician and, due to technical limitations, is unable to accurately distinguish between healthy and pathologic regions. In this paper, we propose two optical approaches for objectively sensing the vocal folds vibrations, using either external or internal laser illumination, based on temporal tracking of the reflected spatial distribution of secondary speckle patterns. The external configuration (the neck) is noninvasive and the internal configuration (the larynx) allows simultaneous extraction of data from multiple sites on the vocal folds. In this paper, we present measurements of healthy human subjects. Quantitative and precise measurements of vibration parameters of the vocal folds will enable a better understanding of hidden pathologies and optimize the diagnosis and treatment.

Demonstration of a Speckle Based Sensing with Pulse-Doppler Radar for Vibration Detection

In previous works, an optical technique for extraction and separation of remote static vibrations has been demonstrated. In this paper, we will describe an approach in which RF speckle movement is used to extract remote vibrations of a static target. The use of conventional radar Doppler methods is not suitable for detecting vibrations of static targets. In addition, the speckle method has an important advantage, in that it is able to detect vibrations at far greater distances than what is normally detected in classical optical methods. The experiment described in this paper was done using a motorized vehicle, which engine was turned on and off. The results showed that the system was able to distinguish between the different engine states, and in addition, was able to determine the vibration frequency of the engine. The first step towards real time detection of human vital signs using RF speckle patterns is presented.

Noncontact speckle-based optical sensor for detection of glucose concentration using magneto-optic effect

We experimentally verify a speckle-based technique for noncontact measurement of glucose concentration in the bloodstream. The final device is intended to be a single wristwatch-style device containing a laser, a camera, and an alternating current (ac) electromagnet generated by a solenoid. The experiments presented are performed in vitro as proof of the concept. When a glucose substance is inserted into a solenoid generating an ac magnetic field, it exhibits Faraday rotation, which affects the temporal changes of the secondary speckle pattern distributions. The temporal frequency resulting from the ac magnetic field was found to have a lock-in amplification role, which increased the observability of the relatively small magneto-optic effect. Experimental results to support the proposed concept are presented.

Optical configuration of pigmented lesion detection by frequency analysis of skin speckle patterns

In this paper we present a novel approach of realizing a safe, simple, and inexpensive sensor applicable to pigmented lesions detection. The approach is based on temporal tracking of back-reflected secondary speckle patterns generated while illuminating the affected area with a laser and applying periodic pressure to the surface via a controlled vibration source. When applied to pigmented lesions, the technique is superior to visual examination in avoiding many false positives and resultant unnecessary biopsies. Applying a series of different vibration frequencies at the examined tissue and analyzing the 2-D time varying speckle patterns in response to the applied periodic pressure creates a unique signature for each and different pigmented lesion. Analyzing these signatures is the first step toward detection of malignant melanoma. In this paper we present preliminary experiments that show the validity of the developed sensor for the classification of pigmented lesions.

Speckle-learning-based object recognition through scattering media

We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.