Emergency Department-Based Physical Function Measures for Falls in Older Adults and Outcomes: A Secondary Analysis of GAPcare.

BACKGROUND AND PURPOSE: Falls are the leading reason for injury-related emergency department (ED) visits for older adults. The Geriatric Acute and Post-acute Fall Prevention Intervention (GAPcare), an in-ED intervention combining a medication therapy management session delivered by a pharmacist and a fall risk assessment and plan by a physical therapist, reduced ED revisits at 6 months among older adults presenting after a fall. Our objective was to evaluate the relationship between measures of function obtained in the ED and clinical outcomes. METHODS: This was a secondary analysis of data from GAPcare, a randomized controlled trial conducted from January 2018 to October 2019 at 2 urban academic EDs. Standardized measures of function (Timed Up and Go [TUG] test, Barthel Activity of Daily Living [ADL], Activity Measure for Post Acute Care [AM-PAC] 6 clicks) were collected at the ED index visit. We performed a descriptive analysis and hypothesis testing (chi square test and analysis of variance) to assess the relationship of functional measures with outcomes (ED disposition, ED revisits for falls, and place of residence at 6 months). Emergency department disposition status refers to discharge location immediately after the ED evaluation is complete (eg, hospital admission, original residence, skilled nursing facility). RESULTS AND DISCUSSION: Among 110 participants, 55 were randomized to the GAPcare intervention and 55 received usual care. Of those randomized to the intervention, 46 received physical therapy consultation. Median age was 81 years; participants were predominantly women (67%) and White (94%). Seventy-three (66%) were discharged to their original residence, 14 (13%) were discharged to a skilled nursing facility and 22 (20%) were admitted. There was no difference in ED disposition status by index visit Barthel ADLs (P = .371); however, TUG times were faster (P = .016), and AM-PAC 6 clicks score was higher among participants discharged to their original residence (P ≤ .001). Participants with slower TUG times at the index ED visit were more likely to reside in nursing homes by six months (P = .002), while Barthel ADL and AM-PAC 6 clicks did not differ between those residing at home and other settings. CONCLUSIONS: Measures of function collected at the index ED visit, such as the AM-PAC 6 clicks and TUG time, may be helpful at predicting clinical outcomes for older adults presenting for a fall. Based on our study findings, we suggest a novel workflow to guide the use of these clinical measures for ED patients with falls.

The role of attention in immersion: The two-competitor model.

Currently, we face an exponentially increasing interest in immersion, especially sensory-driven immersion, mainly due to the rapid development of ideas and business models centered around a digital virtual universe as well as the increasing availability of affordable immersive technologies for education, communication, and entertainment. However, a clear definition of 'immersion', in terms of established neurocognitive concepts and measurable properties, remains elusive, slowing research on the human side of immersive interfaces. To address this problem, we propose a conceptual, taxonomic model of attention in immersion. We argue (a) modeling immersion theoretically as well as studying immersion experimentally requires a detailed characterization of the role of attention in immersion, even though (b) attention, while necessary, cannot be a sufficient condition for defining immersion. Our broader goal is to characterize immersion in terms that will be compatible with established psychophysiolgical measures that could then in principle be used for the assessment and eventually the optimization of an immersive experience. We start from the perspective that immersion requires the projection of attention to an induced reality, and build on accepted taxonomies of different modes of attention for the development of our two-competitor model. The two-competitor model allows for a quantitative implementation and has an easy graphical interpretation. It helps to highlight the important link between different modes of attention and affect in studying immersion.

Adapting virus filtration to continuous processing: Effects of product and process variability on filtration performance.

Virus filtration (VF) is an important unit operation in the manufacture of biotherapeutics that provides robust removal of potential virus contaminants. Small virus removal can be impacted by the low operating pressures and potential depressurization events that are often associated with continuous operations where increased operational flexibility for higher loading at low flux and low pressure is required. In this study, we evaluated the impact of low flux (7 LMH) and pressure interruptions on minute virus of mice (MVM) removal. We used long-term filtrations conducted to a target throughput of 1000 L/m2 with four different monoclonal antibodies on small-scale hollow fiber virus filters with a hydrophilic modified polyvinylidene fluoride membrane. These conditions are certainly challenging for any VF operation and ensuring robust viral clearance under such conditions is critical to the design and implementation of continuous VF. Planova BioEX filters effectively removed MVM at 4 log or greater when run continuously for up to 6 days. Interestingly, pressure increases associated with filter fouling over the duration of long-term filtrations were shown to be reflective of load material variability and could be remediated by implementation of an inline prefilter. Pressure interruptions had minimal impact on overall MVM logarithmic reduction value. Effective virus removal was achieved with pressure increases being largely product-specific, which demonstrates the capability of the virus filter to remove virus independent of pressure increases that are expected to occur with increased protein load.

Assessment of Vestigial Auriculomotor Activity to Acoustic Stimuli Using Electrodes In and Around the Ear.

Recently, it has been demonstrated that electromyographic (EMG) activity of auricular muscles in humans, especially the postauricular muscle (PAM), depends on the spatial location of auditory stimuli. This observation has only been shown using wet electrodes placed directly on auricular muscles. To move towards a more applied, out-of-the-laboratory setting, this study aims to investigate if similar results can be obtained using electrodes placed in custom-fitted earpieces. Furthermore, with the exception of the ground electrode, only dry-contact electrodes were used to record EMG signals, which require little to no skin preparation and can therefore be applied extremely fast. In two experiments, auditory stimuli were presented to ten participants from different spatial directions. In experiment 1, stimuli were rapid onset naturalistic stimuli presented in silence, and in experiment 2, the corresponding participant's first name, presented in a "cocktail party" environment. In both experiments, ipsilateral responses were significantly larger than contralateral responses. Furthermore, machine learning models objectively decoded the direction of stimuli significantly above chance level on a single trial basis (PAM: ≈ 80%, in-ear: ≈ 69%). There were no significant differences when participants repeated the experiments after several weeks. This study provides evidence that auricular muscle responses can be recorded reliably using an almost entirely dry-contact in-ear electrode system. The location of the PAM, and the fact that in-ear electrodes can record comparable signals, would make hearing aids interesting devices to record these auricular EMG signals and potentially utilize them as control signals in the future.

Improvement in Parkinson Disease Symptoms After Treatment for COVID-19 with Monoclonal Antibodies.

BACKGROUND: Parkinson disease (PD) is a neurodegenerative disease characterized by motor symptoms, such as bradykinesia, and non-motor symptoms, such as fatigue, which can be a particularly disabling feature of the disease. METHODS: We conducted a retrospective chart review on a patient who reported improvement in baseline PD symptoms after COVID-19 treatment. RESULTS: The patient is a 76-year-old male with a six-year history of PD who developed a COVID-19 infection, underwent treatment with COVID-19 monoclonal antibodies, and experienced a remarkable improvement in his pre-COVID PD symptoms, most notably his gait and fatigue. Prior to COVID, he rated his fatigue as '9 out of 10,' which worsened to 10 out of 10 during his COVID infection, and post-COVID treatment, his fatigue improved to '3 out of 10'. PRINCIPAL CONCLUSIONS: We described an unexpected improvement in baseline PD symptoms for a patient treated with COVID-19 monoclonal antibodies. Further investigation will be essential to understand the mechanisms underlying this phenomenon.

[New perspectives in orthopedics : Developments through neurotechnology and metaverse]. / Neue Perspektiven in der Orthopädie : Entwicklungen durch Neurotechnologie und Metaversum.

The combination of neurotechnology and metaverse holds high potentials for orthopedics, as it offers a broad spectrum of possibilities to overcome the limits of traditional medical care. The vision of a medical metaverse providing the infrastructure as a link for innovative technologies opens up new opportunities for therapy, medical collaborations and practical, personalized training for aspiring physicians. However, risks and challenges, such as security and privacy, health-related issues, acceptance by patients and doctors, as well as technical hurdles and access to the technologies, remain. Hence, future research and development is paramount. Nonetheless, due to technological progress, the exploration of new research areas, and the improved availability of the technologies paired with cost reduction, the prospects for neurotechnology and metaverse in orthopedics are promising.

Serial virus filtration: A case study evaluating the product-dependent impact of control strategies on process efficiency.

The production of biopharmaceutical products carries an inherent risk of contamination by adventitious viruses. Historically, these manufacturing processes have incorporated a dedicated virus filtration step to ensure product safety. However, challenging process conditions can lead to passage of small viruses to the permeate pool and an overall decrease in the desired virus logarithmic reduction value (LRV) for the process. The implementation of serial virus filtration has improved the robustness of such processes, albeit concerns about increased operating times and process complexity have limited its implementation. This work focused on optimizing a serial filtration process and identifying process control strategies to provide maximum efficiency while ensuring proper controls for process complexity. Constant TMP was identified as the optimal control strategy, which combined with the optimal filter ratio, resulted in a robust and faster virus filtration process. To demonstrate this hypothesis, data with two filters connected in series (1:1 filter ratio) are presented for a representative non-fouling molecule. Similarly, for a fouling product, the optimal setup was a combination of a filter connected in series to two filters operated in parallel (2:1 filter ratio). The optimized filter ratios bring cost- and time-savings benefits to the virus filtration step, thereby offering improved productivity. The results of risk and cost analyses performed as part of this study combined with the control strategy, offer companies a toolbox of strategies to accommodate products with different filterability profiles in their downstream processes. This work demonstrates that the safety advantages of performing filters in series can be achieved with minimal increases in time, cost, and risk.

Speech Tracking in Complex Auditory Scenes with Differentiated In- and Out-Field-Of-View Processing in Hearing Aids.

In naturalistic auditory scenes, relevant information is rarely concentrated at a single location, but rather unpredictably scattered in- and out-field-of-view (in-/out-FOV). Although the parsing of a complex auditory scene is a fairly simple job for a healthy human auditory system, the uncertainty represents a major issue in the development of effective hearing aid (HA) processing strategies. Whereas traditional omnidirectional microphones (OM) amplify the complete auditory scene without enhancing signal-to-noise-ratio (SNR) between in- and out-FOV streams, directional microphones (DM) may greatly increase SNR at the cost of preventing HA users to perceive out-FOV information. The present study compares the conventional OM and DM HA settings to a split processing (SP) scheme differentiating between in- and out-FOV processing. We recorded electroencephalographic data of ten young, normal-hearing listeners who solved a cocktail-party-scenario-paradigm with continuous auditory streams and analyzed neural tracking of speech with a stimulus reconstruction (SR) approach. While results for all settings exhibited significantly higher SR accuracies for attended in-FOV than unattended out-FOV streams, there were distinct differences between settings. In-FOV SR performance was dominated by DM and SP and out-FOV SR accuracies were significantly higher for SP compared to OM and DM. Our results demonstrate the potential of a SP approach to combine the advantages of traditional OM and DM settings without introduction of significant compromises.

Motion Sickness related Route Profiling for Evaluation of the Sensory Conflict in Real-Driving Studies.

The risk for passengers of an automated vehicle to suffer from motion sickness symptoms increases while performing non-driving tasks. Motion sickness, whether at sea, in the air, in a car or in virtual reality, has been studied for years, but the specific motion patterns of different vehicles and the individual physiology of passengers complicate the definition of general applicable models. Technical progress in vehicles, e.g. the development of the chassis or general digitalization, is constantly changing the influences and marginal effects of motion sickness. In recent years, increasing number of investigations concentrated on the influencing factors on motion sickness. However, the relation between emesis and vehicle dynamics itself is predominantly inadequately presented. Therefore, the results can poorly be incorporate in mathematical models of the sensory conflict theory established as leading theory in the research community. In our research, we suggest a method to prepare and present route and driving information to increase the transparency of real-world driving experiments. We used determined position-based spectrograms to simplify the understanding of the provoked acceleration as well as frequency, known as important motion sickness trigger. Standardized use of this method would support review articles about driving experiments and thus support research regarding motion sickness prediction and occurrence in vehicles.

Lagrangian Motion Magnification with Landmark-Prior and Sparse PCA for Facial Microexpressions and Micromovements.

Video motion magnification methods are motion visualization techniques that aim to magnify subtle and imper-ceptibly small motions in videos. They fall into two main groups where Eulerian methods work on the pixel grid with implicit motion information and Lagrangian methods use explicitly estimated motion and modify point trajectories. The motion in high framerate videos of faces can contain a wide variety of information that ranges from microexpressions over pulse or respiratory rate to cues on speech and affective state. In his work, we propose a novel strategy for Lagrangian motion magnification that integrates landmark information from the face as well as an approach to decompose facial motions in an unsupervised manner using sparse PCA. We decompose the estimated displacements into different movement components that are subsequently amplified selectively. We propose two approaches: A landmark-based decomposition into global and local movements and a decomposition into multiple coherent motion components based on sparse PCA. Optical flow estimation is performed using a state-of-the-art deep learning-based method that we retrain on a microexpression database. Clinical relevance- This method could be applied to the annotation and analysis of micromovements for neurocognitive assessment and even novel, medical applications where micro-motions of the face might play a role.

Leveraging Mobile-Based Sensors for Clinical Research to Obtain Activity and Health Measures for Disease Monitoring, Prevention, and Treatment.

Clinical researchers are using mobile-based sensors to obtain detailed and objective measures of the activity and health of research participants, but many investigators lack expertise in integrating wearables and sensor technologies effectively into their studies. Here, we describe the steps taken to design a study using sensors for disease monitoring in older adults and explore the benefits and drawbacks of our approach. In this study, the Geriatric Acute and Post-acute Fall Prevention Intervention (GAPcare), we created an iOS app to collect data from the Apple Watch's gyroscope, accelerometer, and other sensors; results of cognitive and fitness tests; and participant-entered survey data. We created the study app using ResearchKit, an open-source framework developed by Apple for medical research that includes neuropsychological tests (e.g., of executive function and memory), gait speed, balance, and other health assessments. Data is transmitted via an Application Programming Interface (API) from the app to REDCap for researchers to monitor and analyze in real-time. Employing the lessons learned from GAPcare could help researchers create study-tailored research apps and access timely information about their research participants from wearables and smartphone devices for disease prevention, monitoring, and treatment.

Strategies to Ensure Continuity of Care Using Telemedicine with Older Adults during COVID-19: A Qualitative Study of Physicians in Primary Care and Geriatrics.

Objectives: Our objective was to interview primary care physicians (PCPs) and geriatricians on their experiences using telemedicine during the COVID-19 pandemic to examine strategies used to maintain continuity of care with their patients, ages 65 and older. Methods: Using purposive sampling, we selected physicians based on community size (metro/suburban/rural) and practice setting (academic/community) and conducted semi-structured interviews via Zoom (mean: 30 minutes). Interviews were recorded, transcribed, coded, and analyzed using framework analysis. Results: We enrolled 33 physicians (15 PCPs and 18 geriatricians) from July to November 2020. Findings indicate that many physicians successfully bridged the digital divide by: assessing patients' technological readiness in advance, being flexible with telehealth modes, using available home or facility-based staff, educating patients on telehealth privacy and usefulness, making accommodations for disabilities, and involving caregivers. Discussion: These findings can inform future policy and practice and assist physicians in resolving addressable barriers to telehealth use among older patients.

Software for non-parametric image registration of 2-photon imaging data.

Functional 2-photon microscopy is a key technology for imaging neuronal activity. The recorded image sequences, however, can contain non-rigid movement artifacts which requires high-accuracy movement correction. Variational optical flow (OF) estimation is a group of methods for motion analysis with established performance in many computer vision areas. However, it has yet to be adapted to the statistics of 2-photon neuroimaging data. In this work, we present the motion compensation method Flow-Registration that outperforms previous alignment tools and allows to align and reconstruct even low signal-to-noise ratio 2-photon imaging data and is able to compensate high-divergence displacements during local drug injections. The method is based on statistics of such data and integrates previous advances in variational OF estimation. Our method is available as an easy-to-use ImageJ/FIJI plugin as well as a MATLAB toolbox with modular, object oriented file IO, native multi-channel support and compatibility with existing 2-photon imaging suites.

Telehealth was beneficial during COVID-19 for older Americans: A qualitative study with physicians.

BACKGROUND: Individuals aged 65 and older face unique barriers to adoption of telehealth, and the coronavirus disease 2019 pandemic has provided a "natural experiment" in how to meet the health needs of older patients remotely. Physician perspectives on practical considerations surrounding telehealth adoption, motivations of use, and reasons for nonuse are necessary to inform the future of healthcare delivery. The objective is to understand the experiences of physicians using telemedicine for older patients. METHODS: From September to November 2020, we conducted 30-min semi-structured interviews using purposeful sampling to identify and enroll participants from diverse settings. We included 48 U.S.-based physicians (geriatrician, n = 18, primary care, n = 15, emergency, n = 15) from all geographic regions, rural-urban and academic/community settings. Audio-recorded interviews were professionally transcribed and analyzed using framework analysis. Major themes and subthemes were identified. RESULTS: Participants had a median (interquartile range) age of 37.5 (34-44.5), 27 (56%) were women. Five major themes emerged: (1) telehealth uptake was rapid and iterative, (2) telehealth improved the safety of medical care, (3) use cases were specialty-specific (for geriatricians and primary care physicians telehealth substituted for in-person visits; for emergency physicians it primarily supplemented in-person visits), (4) physicians altered clinical care to overcome older patient barriers to telehealth use, and (5) telehealth use among physicians declined in mid-April 2020, due primarily to patient needs and administrator preferences, not physician factors. CONCLUSION: In this qualitative analysis, physicians reported a rapid, iterative uptake of telehealth and attenuation of use as coronavirus disease 2019 prevalence declined. Physician experiences during the pandemic can inform interventions and policies to help buoy telehealth for ongoing healthcare delivery and ensure its accessibility for older Americans.

Virus filter scalability: Demonstration of consistent viral clearance across laboratory and manufacturing scales.

Virus removal filtration processes in biopharmaceutical manufacturing are developed, optimized and validated for viral clearance using laboratory scale filters. Thus, the scalability of these filters is critical for accurately extrapolating filtration performance and reliably extending viral clearance to manufacturing scale. Virus removal filter manufacturers generally validate scalability of filtration performance based on various filtration parameters, and virus removal capability is extended to manufacturing scale filters using inert, size-appropriate particles such as gold nanoparticles to avoid the risks associated with using mammalian viruses in large feed volumes. In this study, we use bacteriophage PP7 as a parvovirus model to directly demonstrate viral clearance on Planova™ BioEX virus removal filters across all scales, including manufacturing scale. Filters with hollow fibers from three spinning series with filter sizes ranging from 0.0003 to 4.0 m2 were tested for virus removal, flux, and protein recovery performance using BSA spiked with PP7. Complete viral clearance was observed across all filter sizes with PP7 LRV of ≥4.7 or higher. Flux and protein recovery were also consistent. These results demonstrate the scalability of filtration performance and consistent virus removal at all sizes, supporting the use of laboratory scale filters to validate viral clearance at manufacturing scales.

Derivation and Validation of a Predictive Algorithm for Long-Term Care Admission or Death.

OBJECTIVES: Older veterans prefer to remain in their homes and communities as long as possible. Although targeted delivery of home- and community-based services for veterans might delay long-term care placement, often, access to these services is inconsistently organized or delayed. To aid in early recognition of veterans at high risk for long-term care placement or death, we developed and validated a predictive algorithm, "Choose Home." DESIGN: A retrospective observational cohort analysis was used. SETTING AND PARTICIPANTS: Two cohorts of Veterans Health Administration (VHA; a large integrated health care system) users were assembled: Derivation (4.6 million) and Confirmation (4.7 million). The Derivation Cohort included Veterans Administration users from fiscal year 2013; the Confirmation Cohort included Veterans Administration users from fiscal year 2014. METHODS: A total of 148 predictor variables, including demographics, comorbidities, and utilizations were selected using logistic regression to predict placement in a long-term care facility for >90 days or death within 2 years. RESULTS: Veterans were predominantly male [92.8% (Derivation), 92.5% (Confirmation)] and older [61.7±15.5 (Derivation), 61.5±15.6 years (Confirmation)], with a high prevalence of comorbid conditions. Between the Derivation and Confirmation Cohorts, the areas under the receiver operating characteristic curves were found to be 0.80 [95% confidence interval (CI) 0.799, 0.802] and 0.80 (95% CI 0.800, 0.802), respectively, indicating good discrimination for determining at-risk veterans. CONCLUSIONS AND IMPLICATIONS: We created a predictive algorithm that identifies veterans at highest risk for long-term institutionalization or death. This algorithm provides clinicians with information that can proactively inform clinical decision making and care coordination. This study provides the groundwork for future investigations on how home- and community-based services can target older adults at highest risk to extend time in their communities.

Multimodal data acquisition at SARS-CoV-2 drive through screening centers: Setup description and experiences in Saarland, Germany.

SARS-CoV-2 drive through screening centers (DTSC) have been implemented worldwide as a fast and secure way of mass screening. We use DTSCs as a platform for the acquisition of multimodal datasets that are needed for the development of remote screening methods. Our acquisition setup consists of an array of thermal, infrared and RGB cameras as well as microphones and we apply methods from computer vision and computer audition for the contactless estimation of physiological parameters. We have recorded a multimodal dataset of DTSC participants in Germany for the development of remote screening methods and symptom identification. Acquisition in the early stages of a pandemic and in regions with high infection rates can facilitate and speed up the identification of infection specific symptoms and large-scale data acquisition at DTSC is possible without disturbing the flow of operation.

The Geriatric Acute and Post-Acute Fall Prevention Intervention (GAPcare) II to Assess the Use of the Apple Watch in Older Emergency Department Patients With Falls: Protocol for a Mixed Methods Study.

BACKGROUND: Falls are a common problem among older adults that lead to injury, emergency department (ED) visits, and institutionalization. The Apple Watch can detect falls and alert caregivers and clinicians that help is needed; the device could also be used to objectively collect data on gait, fitness, and falls as part of clinical trials. However, little is known about the ease of use of this technology among older adult ED patients, a population at high risk of recurrent falls. OBJECTIVE: The goal of this study-the Geriatric Acute and Post-Acute Fall Prevention Intervention (GAPcare) II-is to examine the feasibility, acceptability, and usability of the Apple Watch Series 4 paired with the iPhone and our research app Rhode Island FitTest (RIFitTest) among older adult ED patients seeking care for falls. METHODS: We will conduct field-testing with older adult ED patients (n=25) who sustained a fall and their caregivers (n=5) to determine whether they can use the Apple Watch, iPhone, and app either (1) continuously or (2) periodically, with or without telephone assistance from the research staff, to assess gait, fitness, and/or falls over time. During the initial encounter, participants will receive training in the Apple Watch, iPhone, and our research app. They will receive an illustrated training manual and a number to call if they have questions about the research protocol or device usage. Participants will complete surveys and cognitive and motor assessments on the app during the study period. At the conclusion of the study, we will solicit participant feedback through semistructured interviews. Qualitative data will be summarized using framework matrix analyses. Sensor and survey response data will be analyzed using descriptive statistics. RESULTS: Recruitment began in December 2019 and was on pause from April 2020 until September 2020 due to the COVID-19 pandemic. Study recruitment will continue until 30 participants are enrolled. This study has been approved by the Rhode Island Hospital Institutional Review Board (approval 1400781-16). CONCLUSIONS: GAPcare II will provide insights into the feasibility, acceptability, and usability of the Apple Watch, iPhone, and the RIFitTest app in the population most likely to benefit from the technology: older adults at high risk of recurrent falls. In the future, wearables could be used as part of fall prevention interventions to prevent injury before it occurs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04304495; https://clinicaltrials.gov/ct2/show/NCT04304495. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24455.

Speech induced binaural beats: Electrophysiological assessment of binaural interaction.

This paper introduces and evaluates a speech signal manipulation scheme that generates transient speech induced binaural beats (SBBs). These SBBs can only be perceived when different signals are presented dichotically (to both ears). Event-related potentials were recorded in 22 normal-hearing subjects. Dichotic stimulus presentation reliably evoked auditory late responses (ALRs) in all subjects using such manipulated signals. As control measurements, diotic stimulation modalities were presented to confirm that the ALRs were not evoked by the speech signal itself or that the signal manipulation scheme created audible artifacts. Since diotic measurements evoked no ALRs, responses from dichotic stimulation are a pure correlate of binaural interaction. While there are several auditory stimuli (mostly modulated sinusoids or noise) that share this characteristic, none of them are based on running speech. Because SBBs can be added to any arbitrary speech signal, they could easily be combined with psychoacoustic tests, for example speech reception thresholds, adding an objective measure of binaural interaction.

Fast variational alignment of non-flat 1D displacements for applications in neuroimaging.

BACKGROUND: In the context of signal analysis and pattern matching, alignment of 1D signals for the comparison of signal morphologies is an important problem. For image processing and computer vision, 2D optical flow (OF) methods find wide application for motion analysis and image registration and variational OF methods have been continuously improved over the past decades. NEW METHOD: We propose a variational method for the alignment and displacement estimation of 1D signals. We pose the estimation of non-flat displacements as an optimization problem with a similarity and smoothness term similar to variational OF estimation. To this end, we can make use of efficient optimization strategies that allow real-time applications on consumer grade hardware. RESULTS: We apply our method to two applications from functional neuroimaging: The alignment of 2-photon imaging line scan recordings and the denoising of evoked and event-related potentials in single trial matrices. We can report state of the art results in terms of alignment quality and computing speeds. EXISTING METHODS: Existing methods for 1D alignment target mostly constant displacements, do not allow native subsample precision or precise control over regularization or are slower than the proposed method. CONCLUSIONS: Our method is implemented as a MATLAB toolbox and is online available. It is suitable for 1D alignment problems, where high accuracy and high speed is needed and non-constant displacements occur.