The Ultra-Long-Term Sleep study: Design, rationale, data stability and user perspective.

Sleep deprivation and poor sleep quality are significant societal challenges that negatively impact individuals' health. The interaction between subjective sleep quality, objective sleep measures, physical and cognitive performance, and their day-to-day variations remains poorly understood. Our year-long study of 20 healthy individuals, using subcutaneous electroencephalography, aimed to elucidate these interactions, assessing data stability and participant satisfaction, usability, well-being and adherence. In the study, 25 participants were fitted with a minimally invasive subcutaneous electroencephalography lead, with 20 completing the year of subcutaneous electroencephalography recording. Signal stability was measured using covariance of variation. Participant satisfaction, usability and well-being were measured with questionnaires: Perceived Ease of Use questionnaire, System Usability Scale, Headache questionnaire, Major Depression Inventory, World Health Organization 5-item Well-Being Index, and interviews. The subcutaneous electroencephalography signals remained stable for the entire year, with an average participant adherence rate of 91%. Participants rated their satisfaction with the subcutaneous electroencephalography device as easy to use with minimal or no discomfort. The System Usability Scale score was high at 86.3 ± 10.1, and interviews highlighted that participants understood how to use the subcutaneous electroencephalography device and described a period of acclimatization to sleeping with the device. This study provides compelling evidence for the feasibility of longitudinal sleep monitoring during everyday life utilizing subcutaneous electroencephalography in healthy subjects, showcasing excellent signal stability, adherence and user experience. The amassed subcutaneous electroencephalography data constitutes the largest dataset of its kind, and is poised to significantly advance our understanding of day-to-day variations in normal sleep and provide key insights into subjective and objective sleep quality.

Subclinical epileptiform discharges in Alzheimer's disease are associated with increased hippocampal blood flow.

BACKGROUND: In epilepsy, the ictal phase leads to cerebral hyperperfusion while hypoperfusion is present in the interictal phases. Patients with Alzheimer's disease (AD) have an increased prevalence of epileptiform discharges and a study using intracranial electrodes have shown that these are very frequent in the hippocampus. However, it is not known whether there is an association between hippocampal hyperexcitability and regional cerebral blood flow (rCBF). The objective of the study was to investigate the association between rCBF in hippocampus and epileptiform discharges as measured with ear-EEG in patients with Alzheimer's disease. Our hypothesis was that increased spike frequency may be associated with increased rCBF in hippocampus. METHODS: A total of 24 patients with AD, and 15 HC were included in the analysis. Using linear regression, we investigated the association between rCBF as measured with arterial spin-labelling MRI (ASL-MRI) in the hippocampus and the number of spikes/sharp waves per 24 h as assessed by ear-EEG. RESULTS: No significant difference in hippocampal rCBF was found between AD and HC (p-value = 0.367). A significant linear association between spike frequency and normalized rCBF in the hippocampus was found for patients with AD (estimate: 0.109, t-value = 4.03, p-value < 0.001). Changes in areas that typically show group differences (temporal-parietal cortex) were found in patients with AD, compared to HC. CONCLUSIONS: Increased spike frequency was accompanied by a hemodynamic response of increased blood flow in the hippocampus in patients with AD. This phenomenon has also been shown in patients with epilepsy and supports the hypothesis of hyperexcitability in patients with AD. The lack of a significant difference in hippocampal rCBF may be due to an increased frequency of epileptiform discharges in patients with AD. TRIAL REGISTRATION: The study is registered at clinicaltrials.gov (NCT04436341).

Subclinical Epileptiform Activity in Dementia with Lewy Bodies.

BACKGROUND: Patients with dementia with Lewy bodies (DLB) have a higher probability of seizures than in normal aging and in other types of neurodegenerative disorders. Depositions of α-synuclein, a pathological hallmark of DLB, can induce network excitability, which can escalate into seizure activity. Indicator of seizures are epileptiform discharges as observed using electroencephalography (EEG). However, no studies have so far investigated the occurrence of interictal epileptiform discharges (IED) in patients with DLB. OBJECTIVES: To investigate if IED as measured with ear-EEG occurs with a higher frequency in patients with DLB compared to healthy controls (HC). METHODS: In this longitudinal observational exploratory study, 10 patients with DLB and 15 HC were included in the analysis. Patients with DLB underwent up to three ear-EEG recordings, each lasting up to 2 days, over a period of 6 months. RESULTS: At baseline, IED were detected in 80% of patients with DLB and in 46.7% of HC. The spike frequency (spikes or sharp waves/24 hours) was significantly higher in patients with DLB as compared to HC with a risk ratio of 2.52 (CI, 1.42-4.61; P-value = 0.001). Most IED occurred at night. CONCLUSIONS: Long-term outpatient ear-EEG monitoring detects IED in most patients with DLB with an increased spike frequency compared to HC. This study extends the spectrum of neurodegenerative disorders in which epileptiform discharges occurs at an elevated frequency. It is possible that epileptiform discharges are, therefore, a consequence of neurodegeneration. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Detection of subclinical epileptiform discharges in Alzheimer's disease using long-term outpatient EEG monitoring.

BACKGROUND: In patients with Alzheimer's disease (AD) without clinical seizures, up to half have epileptiform discharges on long-term in-patient electroencephalography (EEG) recordings. Long-term in-patient monitoring is obtrusive, and expensive as compared to outpatient monitoring. No studies have so far investigated if long-term outpatient EEG monitoring is able to identify epileptiform discharges in AD. Our aim is to investigate if epileptiform discharges as measured with ear-EEG are more common in patients with AD compared to healthy elderly controls (HC). METHODS: In this longitudinal observational study, 24 patients with mild to moderate AD and 15 age-matched HC were included in the analysis. Patients with AD underwent up to three ear-EEG recordings, each lasting up to two days, within 6 months. RESULTS: The first recording was defined as the baseline recording. At baseline, epileptiform discharges were detected in 75.0% of patients with AD and in 46.7% of HC (p-value = 0.073). The spike frequency (spikes or sharp waves/24 h) was significantly higher in patients with AD as compared to HC with a risk ratio of 2.90 (CI: 1.77-5.01, p < 0.001). Most patients with AD (91.7%) showed epileptiform discharges when combining all ear-EEG recordings. CONCLUSIONS: Long-term ear-EEG monitoring detects epileptiform discharges in most patients with AD with a three-fold increased spike frequency compared to HC, which most likely originates from the temporal lobes. Since most patients showed epileptiform discharges with multiple recordings, elevated spike frequency should be considered a marker of hyperexcitability in AD.

Long-term ear-EEG monitoring of sleep - A case study during shift work.

The interest in sleep as a potential clinical biomarker is growing, but the standard method of sleep assessment, polysomnography, is expensive, time consuming, and requires a lot of expert assistance for both set-up and interpretation. To make sleep analysis more available both in research and in the clinic, there is a need for a reliable wearable device for sleep staging. In this case study, we test ear-electroencephalography. A wearable, where electrodes are placed in the outer ear, as a platform for longitudinal at-home recording of sleep. We explore the usability of the ear-electroencephalography in a shift work case with alternating sleep conditions. We find the ear-electroencephalography platform to be reliable both in terms of showing substantial agreement to polysomnography after long-time use (with an overall agreement, using Cohen's kappa, of 0.72) and by being unobtrusive enough to wear during night shift conditions. We find that fractions of non-rapid eye movement sleep and transition probability between sleep stages show great potential as sleep metrics when exploring quantitative differences in sleep architecture between shifting sleep conditions. This study shows that the ear-electroencephalography platform holds great potential as a reliable wearable for quantifying sleep "in the wild", pushing this technology further towards clinical adaptation.

Long-Term EEG Monitoring in Patients with Alzheimer's Disease Using Ear-EEG: A Feasibility Study.

BACKGROUND: Previous studies have reported that epileptiform activity may be detectible in nearly half of patients with Alzheimer's disease (AD) on long-term electroencephalographic (EEG) recordings. However, such recordings can be uncomfortable, expensive, and difficult. Ear-EEG has shown promising results for long-term EEG monitoring, but it has not been used in patients with AD. OBJECTIVE: To investigate if ear-EEG is a feasible method for long-term EEG monitoring in patients with AD. METHODS: In this longitudinal, single-group feasibility study, ten patients with mild to moderate AD were recruited. A total of three ear-EEG recordings of up to 48 hours three months apart for six months were planned. RESULTS: All patients managed to wear the ear-EEG for at least 24 hours and at least one full night. A total of 19 ear-EEG recordings were performed (self-reported recording, mean: 37.15 hours (SD: 8.96 hours)). After automatic pre-processing, a mean of 27.37 hours (SD: 7.19 hours) of data with acceptable quality in at least one electrode in each ear was found. Seven out of ten participants experienced mild adverse events. Six of the patients did not complete the study with three patients not wanting to wear the ear-EEG anymore due to adverse events. CONCLUSION: It is feasible and safe to use ear-EEG for long-term EEG monitoring in patients with AD. Minor adjustments to the equipment may improve the comfort for the participants.

Repeated automatic sleep scoring based on ear-EEG is a valuable alternative to manually scored polysomnography.

While polysomnography (PSG) is the gold standard to quantify sleep, modern technology allows for new alternatives. PSG is obtrusive, affects the sleep it is set out to measure and requires technical assistance for mounting. A number of less obtrusive solutions based on alternative methods have been introduced, but few have been clinically validated. Here we validate one of these solutions, the ear-EEG method, against concurrently recorded PSG in twenty healthy subjects each measured for four nights. Two trained technicians scored the 80 nights of PSG independently, while an automatic algorithm scored the ear-EEG. The sleep stages and eight sleep metrics (Total Sleep Time (TST), Sleep Onset Latency, Sleep Efficiency, Wake After Sleep Onset, REM latency, REM fraction of TST, N2 fraction of TST, and N3 fraction of TST) were used in the further analysis. We found the sleep metrics: Total Sleep Time, Sleep Onset Latency, Sleep Efficiency, Wake After Sleep Onset were estimated with high accuracy and precision between automatic sleep scoring and manual sleep scoring. However, the REM latency and REM fraction of sleep showed high accuracy but low precision. Further, the automatic sleep scoring systematically overestimated the N2 fraction of sleep and slightly underestimated the N3 fraction of sleep. We demonstrate that sleep metrics estimated from automatic sleep scoring based on repeated ear-EEG in some cases are more reliably estimated with repeated nights of automatically scored ear-EEG than with a single night of manually scored PSG. Thus, given the obtrusiveness and cost of PSG, ear-EEG seems to be a useful alternative for sleep staging for the single night recording and an advantageous choice for several nights of sleep monitoring.

Investigation of low dimensional feature spaces for automatic sleep staging.

BACKGROUND: Automatic sleep stage classification depends crucially on the selection of a good set of descriptive features. However, the selection of a feature set with an appropriate low computational cost without compromising classification performance is still a challenge. This study attempts to represent sleep EEG patterns using a minimum number of features, without significant performance loss. METHODS: Three feature selection algorithms were applied to a high dimensional feature space comprising 84 features. These methods were based on a bootstrapping approach guided by Gini ranking and mutual information between the features. The algorithms were tested on three scalp electroencephalography (EEG) and one ear-EEG datasets. The relationship between the information carried by different features was investigated using mutual information and illustrated by a graphical clustering tool. RESULTS: The minimum number of features that can represent the whole feature set without performance loss was found to range between 5 and 11 for different datasets. In ear-EEG, 7 features based on Continuous Wavelet Transform (CWT) resulted in similar performance as the whole set whereas in two scalp EEG datasets, the difference between minimal CWT set and the whole set was statistically significant (0.008 and 0.017 difference in average kappa). Features were divided into groups according to the type of information they carry. The group containing relative power features was identified as the most informative feature group in sleep stage classification, whereas the group containing non-linear features was found to be the least informative. CONCLUSIONS: This study showed that EEG sleep staging can be performed based on a low dimensional feature space without significant decrease in sleep staging performance. This is especially important in the case of wearable devices like ear-EEG where low computational complexity is needed. The division of the feature space into groups of features, and the analysis of the distribution of feature groups for different feature set sizes, is helpful in the selection of an appropriate feature set.

Ear-EEG for sleep assessment: a comparison with actigraphy and PSG.

PURPOSE: To assess automatic sleep staging of three ear-EEG setups with different electrode configurations and compare performance with concurrent polysomnography and wrist-worn actigraphy recordings. METHODS: Automatic sleep staging was performed for single-ear, single-ear with ipsilateral mastoid, and cross-ear electrode configurations, and for actigraphy data. The polysomnography data were manually scored and used as the gold standard. The automatic sleep staging was tested on 80 full-night recordings from 20 healthy subjects. The scoring performance and sleep metrics were determined for all ear-EEG setups and the actigraphy device. RESULTS: The single-ear, the single-ear with ipsilateral mastoid setup, and the cross-ear setup performed five class sleep staging with kappa values 0.36, 0.63, and 0.72, respectively. For the single-ear with mastoid electrode and the cross-ear setup, the performance of the sleep metrics, in terms of mean absolute error, was better than the sleep metrics estimated from the actigraphy device in the current study, and also better than current state-of-the-art actigraphy studies. CONCLUSION: A statistically significant improvement in both accuracy and kappa was observed from single-ear to single-ear with ipsilateral mastoid, and from single-ear with ipsilateral mastoid to cross-ear configurations for both two and five-sleep stage classification. In terms of sleep metrics, the results were more heterogeneous, but in general, actigraphy and single-ear with ipsilateral mastoid configuration were better than the single-ear configuration; and the cross-ear configuration was consistently better than both the actigraphy device and the single-ear configuration.

A Methodology for Anatomic Ultrasound Image Diagnostic Quality Assessment.

This paper discusses the methods for the assessment of ultrasound image quality based on our experiences with evaluating new methods for anatomic imaging. It presents a methodology to ensure a fair assessment between competing imaging methods using clinically relevant evaluations. The methodology is valuable in the continuing process of method optimization and guided development of new imaging methods. It includes a three phased study plan covering from initial prototype development to clinical assessment. Recommendations to the clinical assessment protocol, software, and statistical analysis are presented. Earlier uses of the methodology has shown that it ensures validity of the assessment, as it separates the influences between developer, investigator, and assessor once a research protocol has been established. This separation reduces confounding influences on the result from the developer to properly reveal the clinical value. This paper exemplifies the methodology using recent studies of synthetic aperture sequential beamforming tissue harmonic imaging.

System-Level Design of an Integrated Receiver Front End for a Wireless Ultrasound Probe.

In this paper, a system-level design is presented for an integrated receive circuit for a wireless ultrasound probe, which includes analog front ends and beamformation modules. This paper focuses on the investigation of the effects of architectural design choices on the image quality. The point spread function is simulated in Field II from 10 to 160 mm using a convex array transducer. A noise analysis is performed, and the minimum signal-to-noise ratio (SNR) requirements are derived for the low-noise amplifiers (LNAs) and A/D converters (ADCs) to fulfill the design specifications of a dynamic range of 60 dB and a penetration depth of 160 mm in the B-mode image. Six front-end implementations are compared using Nyquist-rate and Σ∆ modulator ADCs. The image quality is evaluated as a function of the depth in terms of lateral full-width at half-maximum (FWHM) and -12-dB cystic resolution (CR). The designs that minimally satisfy the specifications are based on an 8-b 30-MSPS Nyquist converter and a single-bit third-order 240-MSPS Σ∆ modulator, with an SNR for the LNA in both cases equal to 64 dB. The mean lateral FWHM and CR are 2.4% and 7.1% lower for the Σ∆ architecture compared with the Nyquist-rate one. However, the results generally show minimal differences between equivalent architectures. Advantages and drawbacks are finally discussed for the two families of converters.

Clinical evaluation of synthetic aperture harmonic imaging for scanning focal malignant liver lesions.

The purpose of the study was to perform a clinical comparison of synthetic aperture sequential beamforming tissue harmonic imaging (SASB-THI) sequences with a conventional imaging technique, dynamic receive focusing with THI (DRF-THI). Both techniques used pulse inversion and were recorded interleaved using a commercial ultrasound system (UltraView 800, BK Medical, Herlev, Denmark). Thirty-one patients with malignant focal liver lesions (confirmed by biopsy or computed tomography/magnetic resonance) were scanned. Detection of malignant focal liver lesions and preference of image quality were evaluated blinded off-line by eight radiologists. In total, 2,032 evaluations of 127 image sequences were completed. The sensitivity (77% SASB-THI, 76% DRF-THI, p = 0.54) and specificity (71% SASB-THI, 72% DRF-THI, p = 0.67) of detection of liver lesions and the evaluation of image quality (p = 0.63) did not differ between SASB-THI and DRF-THI. This study indicates the ability of SASB-THI in a true clinical setting.

Tissue harmonic synthetic aperture ultrasound imaging.

Synthetic aperture sequential beamforming (SASB) and tissue harmonic imaging (THI) are combined to improve the image quality of medical ultrasound imaging. The technique is evaluated in a comparative study against dynamic receive focusing (DRF). The objective is to investigate if SASB combined with THI improves the image quality compared to DRF-THI. The major benefit of SASB is a reduced bandwidth between the probe and processing unit. A BK Medical 2202 Ultraview ultrasound scanner was used to acquire beamformed RF data for offline evaluation. The acquisition was made interleaved between methods, and data were recorded with and without pulse inversion for tissue harmonic imaging. Data were acquired using a Sound Technology 192 element convex array transducer from both a wire phantom and a tissue mimicking phantom to investigate spatial resolution and penetration. In vivo scans were also performed for a visual comparison. The spatial resolution for SASB-THI is on average 19% better than DRI-THI, and the investigation of penetration showed equally good signal-to-noise ratio. In vivo B-mode scans were made and compared. The comparison showed that SASB-THI reduces the artifact and noise interference and improves image contrast and spatial resolution.

Implementation of a versatile research data acquisition system using a commercially available medical ultrasound scanner.

This paper describes the design and implementation of a versatile, open-architecture research data acquisition system using a commercially available medical ultrasound scanner. The open architecture will allow researchers and clinicians to rapidly develop applications and move them relatively easy to the clinic. The system consists of a standard PC equipped with a camera link and an ultrasound scanner equipped with a research interface. The ultrasound scanner is an easy-to-use imaging device that is capable of generating high-quality images. In addition to supporting the acquisition of multiple data types, such as B-mode, M-mode, pulsed Doppler, and color flow imaging, the machine provides users with full control over imaging parameters such as transmit level, excitation waveform, beam angle, and focal depth. Beamformed RF data can be acquired from regions of interest throughout the image plane and stored to a file with a simple button press. For clinical trials and investigational purposes, when an identical image plane is desired for both an experimental and a reference data set, interleaved data can be captured. This form of data acquisition allows switching between multiple setups while maintaining identical transducer, scanner, region of interest, and recording time. Data acquisition is controlled through a graphical user interface running on the PC. This program implements an interface for third-party software to interact with the application. A software development toolkit is developed to give researchers and clinicians the ability to utilize third-party software for data analysis and flexible manipulation of control parameters. Because of the advantages of speed of acquisition and clinical benefit, research projects have successfully used the system to test and implement their customized solutions for different applications. Three examples of system use are presented in this paper: evaluation of synthetic aperture sequential beamformation, transverse oscillation for blood velocity estimation, and acquisition of spectral velocity data for evaluating aortic aneurysms.

Shadow effects in simulated ultrasound images derived from computed tomography images using a focused beam tracing model.

Simulation of ultrasound images based on computed tomography (CT) data has previously been performed with different approaches. Shadow effects are normally pronounced in ultrasound images, so they should be included in the simulation. In this study, a method to capture the shadow effects has been developed, which makes the simulated ultrasound images appear more realistic. The method using a focused beam tracing model gives diffuse shadows that are similar to the ones observed in measurements on real objects. Ultrasound images of a cod (Gadus morhua) were obtained with a BK Medical 2202 ProFocus ultrasound scanner (BK Medical, Herlev, Denmark) equipped with a dedicated research interface giving access to beamformed radio frequency data. CT images were obtained with an Aquilion ONE Toshiba CT scanner (Toshiba Medical Systems Corp., Tochigi, Japan). CT data were mapped from Hounsfield units to backscatter strength, attenuation coefficients, and characteristic acoustic impedance. The focused beam tracing model was used to create maps of the transmission coefficient and scattering strength maps. Field II was then used to simulate an ultrasound image of 38.9 × 55.3 × 4.5 mm, using 10(6) point scatterers. As there is no quantitative method to assess quality of a simulated ultrasound image compared to a measured one, visual inspection was used for evaluation.

In vivo evaluation of synthetic aperture sequential beamforming.

Ultrasound in vivo imaging using synthetic aperture sequential beamformation (SASB) is compared with conventional imaging in a double blinded study using side-by-side comparisons. The objective is to evaluate if the image quality in terms of penetration depth, spatial resolution, contrast and unwanted artifacts is comparable to conventional imaging. In vivo data was acquired using a ProFocus ultrasound scanner (BK Medical, Herlev, Denmark) and a 192-element 3.5 MHz convex array transducer (Sound Technology Inc., PA, USA). Data were acquired interleaved, ensuring that the exact same anatomical locations were scanned. Eighteen volunteers were scanned abdominally resulting in 85 image sequence pairs. Evaluation of image quality was performed by five medical doctors. Results show that image quality using SASB was significantly better than conventional imaging (p value: <0.01). There was not a significant difference in penetration depth (p value: 0.55). The study supports that in vivo ultrasound imaging using SASB is feasible for abdominal imaging.