Oleksandr Makeyev

Non-invasive monitoring of chewing and swallowing for objective quantification of ingestive behavior

A methodology of studying of ingestive behavior by non-invasive monitoring of swallowing (deglutition) and chewing (mastication) has been developed. The target application for the developed methodology is to study the behavioral patterns of food consumption and producing volumetric and weight estimates of energy intake. Monitoring is non-invasive based on detecting swallowing by a sound sensor located over laryngopharynx or by a bone-conduction microphone and detecting chewing through a below-the-ear strain sensor. Proposed sensors may be implemented in a wearable monitoring device, thus enabling monitoring of ingestive behavior in free-living individuals. In this paper, the goals in the development of this methodology are two-fold. First, a system comprising sensors, related hardware and software for multi-modal data capture is designed for data collection in a controlled environment. Second, a protocol is developed for manual scoring of chewing and swallowing for use as a gold standard. The multi-modal data capture was tested by measuring chewing and swallowing in 21 volunteers during periods of food intake and quiet sitting (no food intake). Video footage and sensor signals were manually scored by trained raters. Inter-rater reliability study for three raters conducted on the sample set of five subjects resulted in high average intra-class correlation coefficients of 0.996 for bites, 0.988 for chews and 0.98 for swallows. The collected sensor signals and the resulting manual scores will be used in future research as a gold standard for further assessment of sensor design, development of automatic pattern recognition routines and study of the relationship between swallowing/chewing and ingestive behavior.

Automatic Detection of Swallowing Events by Acoustical Means for Applications of Monitoring of Ingestive Behavior

Our understanding of etiology of obesity and overweight is incomplete due to lack of objective and accurate methods for monitoring of ingestive behavior (MIB) in the free-living population. Our research has shown that frequency of swallowing may serve as a predictor for detecting food intake, differentiating liquids and solids, and estimating ingested mass. This paper proposes and compares two methods of acoustical swallowing detection from sounds contaminated by motion artifacts, speech, and external noise. Methods based on mel-scale Fourier spectrum, wavelet packets, and support vector machines are studied considering the effects of epoch size, level of decomposition, and lagging on classification accuracy. The methodology was tested on a large dataset (64.5 h with a total of 9966 swallows) collected from 20 human subjects with various degrees of adiposity. Average weighted epoch-recognition accuracy for intravisit individual models was 96.8%, which resulted in 84.7% average weighted accuracy in detection of swallowing events. These results suggest high efficiency of the proposed methodology in separation of swallowing sounds from artifacts that originate from respiration, intrinsic speech, head movements, food ingestion, and ambient noise. The recognition accuracy was not related to body mass index, suggesting that the methodology is suitable for obese individuals.

Toward Objective Monitoring of Ingestive Behavior in Free-living Population

Understanding of eating behaviors associated with obesity requires objective and accurate monitoring of food intake patterns. Accurate methods are available for measuring total energy expenditure and its components in free‐living populations, but methods for measuring food intake in free‐living people are far less accurate and involve self‐reporting or subjective monitoring. We suggest that chews and swallows can be used for objective monitoring of ingestive behavior. This hypothesis was verified in a human study involving 20 subjects. Chews and swallows were captured during periods of quiet resting, talking, and meals of varying size. The counts of chews and swallows along with other derived metrics were used to build prediction models for detection of food intake, differentiation between liquids and solids, and for estimation of the mass of ingested food. The proposed prediction models were able to detect periods of food intake with >95% accuracy and a fine time resolution of 30 s, differentiate solid foods from liquids with >91% accuracy, and predict mass of ingested food with >91% accuracy for solids and >83% accuracy for liquids. In earlier publications, we have shown that chews and swallows can be captured by noninvasive sensors that could be developed into a wearable device. Thus, the proposed methodology could lead to the development of an innovative new way of assessing human eating behavior in free‐living conditions.

Flat image recognition in the process of microdevice assembly

An image recognition system for use in the assembly of microdevices is developed. The system gives an increase in the assembly process precision. A pin-to-hole insertion task was used to test developed system. The system will be used for assembly of microring-based filters.

Ischemia-reperfusion impairs blood-brain barrier function and alters tight junction protein expression in the ovine fetus

The blood-brain barrier is a restrictive interface between the brain parenchyma and the intravascular compartment. Tight junctions contribute to the integrity of the blood-brain barrier. Hypoxic-ischemic damage to the blood-brain barrier could be an important component of fetal brain injury. We hypothesized that increases in blood-brain barrier permeability after ischemia depend upon the duration of reperfusion and that decreases in tight junction proteins are associated with the ischemia-related impairment in blood-brain barrier function in the fetus. Blood-brain barrier function was quantified with the blood-to-brain transfer constant (K(i)) and tight junction proteins by Western immunoblot in fetal sheep at 127 days of gestation without ischemia, and 4, 24, or 48 h after ischemia. The largest increase in K(i) (P<0.05) was 4 h after ischemia. Occludin and claudin-5 expressions decreased at 4 h, but returned toward control levels 24 and 48 h after ischemia. Zonula occludens-1 and -2 decreased after ischemia. Inverse correlations between K(i) and tight junction proteins suggest that the decreases in tight junction proteins contribute to impaired blood-brain barrier function after ischemia. We conclude that impaired blood-brain barrier function is an important component of hypoxic-ischemic brain injury in the fetus, and that increases in quantitatively measured barrier permeability (K(i)) change as a function of the duration of reperfusion after ischemia. The largest increase in permeability occurs 4 h after ischemia and blood-brain barrier function improves early after injury because the blood-brain barrier is less permeable 24 and 48 than 4 h after ischemia. Changes in the tight junction molecular composition are associated with increases in blood-brain barrier permeability after ischemia.

Automatic food intake detection based on swallowing sounds.

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions.

Toward a Noninvasive Automatic Seizure Control System in Rats With Transcranial Focal Stimulations via Tripolar Concentric Ring Electrodes

Epilepsy affects approximately 1% of the world population. Antiepileptic drugs are ineffective in approximately 30% of patients and have side effects. We are developing a noninvasive, or minimally invasive, transcranial focal electrical stimulation system through our novel tripolar concentric ring electrodes to control seizures. In this study, we demonstrate feasibility of an automatic seizure control system in rats with pentylenetetrazole-induced seizures through single and multiple stimulations. These stimulations are automatically triggered by a real-time electrographic seizure activity detector based on a disjunctive combination of detections from a cumulative sum algorithm and a generalized likelihood ratio test. An average seizure onset detection accuracy of 76.14% was obtained for the test set (n = 13). Detection of electrographic seizure activity was accomplished in advance of the early behavioral seizure activity in 76.92% of the cases. Automatically triggered stimulation significantly (p = 0.001) reduced the electrographic seizure activity power in the once stimulated group compared to controls in 70% of the cases. To the best of our knowledge this is the first closed-loop automatic seizure control system based on noninvasive electrical brain stimulation using tripolar concentric ring electrode electrographic seizure activity as feedback.

Neutralizing anti-interleukin-1β antibodies modulate fetal blood-brain barrier function after ischemia.

We have previously shown that increases in blood-brain barrier permeability represent an important component of ischemia-reperfusion related brain injury in the fetus. Pro-inflammatory cytokines could contribute to these abnormalities in blood-brain barrier function. We have generated pharmacological quantities of mouse anti-ovine interleukin-1β monoclonal antibody and shown that this antibody has very high sensitivity and specificity for interleukin-1β protein. This antibody also neutralizes the effects of interleukin-1β protein in vitro. In the current study, we hypothesized that the neutralizing anti-interleukin-1β monoclonal antibody attenuates ischemia-reperfusion related fetal blood-brain barrier dysfunction. Instrumented ovine fetuses at 127 days of gestation were studied after 30 min of carotid occlusion and 24h of reperfusion. Groups were sham operated placebo-control- (n=5), ischemia-placebo- (n=6), ischemia-anti-IL-1β antibody- (n=7), and sham-control antibody- (n=2) treated animals. Systemic infusions of placebo (0.154M NaCl) or anti-interleukin-1β monoclonal antibody (5.1±0.6 mg/kg) were given intravenously to the same sham or ischemic group of fetuses at 15 min and 4h after ischemia. Concentrations of interleukin-1β protein and anti-interleukin-1β monoclonal antibody were measured by ELISA in fetal plasma, cerebrospinal fluid, and parietal cerebral cortex. Blood-brain barrier permeability was quantified using the blood-to-brain transfer constant (Ki) with α-aminoisobutyric acid in multiple brain regions. Interleukin-1β protein was also measured in parietal cerebral cortices and tight junction proteins in multiple brain regions by Western immunoblot. Cerebral cortical interleukin-1β protein increased (P<0.001) after ischemia-reperfusion. After anti-interleukin-1β monoclonal antibody infusions, plasma anti-interleukin-1β monoclonal antibody was elevated (P<0.001), brain anti-interleukin-1β monoclonal antibody levels were higher (P<0.03), and interleukin-1β protein concentrations (P<0.03) and protein expressions (P<0.001) were lower in the monoclonal antibody-treated group than in placebo-treated-ischemia-reperfusion group. Monoclonal antibody infusions attenuated ischemia-reperfusion-related increases in Ki across the brain regions (P<0.04), and Ki showed an inverse linear correlation (r= -0.65, P<0.02) with anti-interleukin-1β monoclonal antibody concentrations in the parietal cortex, but had little effect on tight junction protein expression. We conclude that systemic anti-interleukin-1β monoclonal antibody infusions after ischemia result in brain anti-interleukin-1β antibody uptake, and attenuate ischemia-reperfusion-related interleukin-1β protein up-regulation and increases in blood-brain barrier permeability across brain regions in the fetus. The pro-inflammatory cytokine, interleukin-1β, contributes to impaired blood-brain barrier function after ischemia in the fetus.

Detection of Food Intake from Swallowing Sequences by Supervised and Unsupervised Methods

Studies of food intake and ingestive behavior in free-living conditions most often rely on self-reporting-based methods that can be highly inaccurate. Methods of Monitoring of Ingestive Behavior (MIB) rely on objective measures derived from chewing and swallowing sequences and thus can be used for unbiased study of food intake with free-living conditions. Our previous study demonstrated accurate detection of food intake in simple models relying on observation of both chewing and swallowing. This article investigates methods that achieve comparable accuracy of food intake detection using only the time series of swallows and thus eliminating the need for the chewing sensor. The classification is performed for each individual swallow rather than for previously used time slices and thus will lead to higher accuracy in mass prediction models relying on counts of swallows. Performance of a group model based on a supervised method (SVM) is compared to performance of individual models based on an unsupervised method (K-means) with results indicating better performance of the unsupervised, self-adapting method. Overall, the results demonstrate that highly accurate detection of intake of foods with substantially different physical properties is possible by an unsupervised system that relies on the information provided by the swallowing alone.

High-Frequency Oscillations Recorded on the Scalp of Patients With Epilepsy Using Tripolar Concentric Ring Electrodes

Epilepsy is the second most prevalent neurological disorder (~1% prevalence) affecting ~67 million people worldwide with up to 75% from developing countries. The conventional electroencephalogram is plagued with artifacts from movements, muscles, and other sources. Tripolar concentric ring electrodes automatically attenuate muscle artifacts and provide improved signal quality. We performed basic experiments in healthy humans to show that tripolar concentric ring electrodes can indeed record the physiological alpha waves while eyes are closed. We then conducted concurrent recordings with conventional disc electrodes and tripolar concentric ring electrodes from patients with epilepsy. We found that we could detect high frequency oscillations, a marker for early seizure development and epileptogenic zone, on the scalp surface that appeared to become more narrow-band just prior to seizures. High frequency oscillations preceding seizures were present in an average of 35.5% of tripolar concentric ring electrode data channels for all the patients with epilepsy whose seizures were recorded and absent in the corresponding conventional disc electrode data. An average of 78.2% of channels that contained high frequency oscillations were within the seizure onset or irritative zones determined independently by three epileptologists based on conventional disc electrode data and videos.