Hemm-Ode, Simone
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An online movement and tremor identification algorithm for evaluation during deep brain stimulation
INTRODUCTION: Deep brain stimulation (DBS) is widely used to alleviate symptoms of movement disorders. During intraoperative stimulation the influence of active or passive movements on the neuronal activity is often evaluated but the evaluation remains mostly subjective. The objective of this paper is to investigate the potential of a previously developed Weighted-frequency Fourier Linear combiner and Kalman filter-based recursive algorithm to identify tremor phases and types. METHODS: Ten accelerometer recordings from eight patients were acquired during DBS from which 186 phases were manually annotated into: rest, postural and kinetic phase without tremor, and rest, postural and kinetic phase with tremor. The method first estimates the instantaneous tremor frequency and then decomposes the motion signal into voluntary and tremorous parts. The tremorous part is used to quantify tremor and the voluntary part to differentiate rest, postural and kinetic phases. RESULTS: Instantaneous tremor frequency and amplitude are successfully tracked online. The overall accuracy for tremorous phases only is 89.1% and 76.3% when also non-tremorous phases are considered. Two main misclassification cases are identified and further discussed. CONCLUSION: The results demonstrate the potential of the developed algorithm as an online tremorous movement classifier. It would benefit from a more advanced tremor detector but nevertheless the obtained digital biomarkers offer an evidence-based analysis and could optimize the efficacy of DBS treatment.
Deep brain stimulation: emerging tools for simulation, data analysis, and visualization
Deep brain stimulation (DBS) is a well-established neurosurgical procedure for movement disorders that is also being explored for treatment-resistant psychiatric conditions. This review highlights important consideration for DBS simulation and data analysis. The literature on DBS has expanded considerably in recent years, and this article aims to identify important trends in the field. During DBS planning, surgery, and follow up sessions, several large data sets are created for each patient, and it becomes clear that any group analysis of such data is a big data analysis problem and has to be handled with care. The aim of this review is to provide an update and overview from a neuroengineering perspective of the current DBS techniques, technical aids, and emerging tools with the focus on patient-specific electric field (EF) simulations, group analysis, and visualization in the DBS domain. Examples are given from the state-of-the-art literature including our own research. This work reviews different analysis methods for EF simulations, tractography, deep brain anatomical templates, and group analysis. Our analysis highlights that group analysis in DBS is a complex multi-level problem and selected parameters will highly influence the result. DBS analysis can only provide clinically relevant information if the EF simulations, tractography results, and derived brain atlases are based on as much patient-specific data as possible. A trend in DBS research is creation of more advanced and intuitive visualization of the complex analysis results suitable for the clinical environment.
Naming images in aphasia: effects of illustrative and photographic images on naming performance in people with and without aphasia
Background: Picture naming is a common tool in aphasia diagnosis and therapy. However, opin-ions differ as to which type of image (e.g., photographs, drawings) is most suitable for naming tasks and whether there is a difference on naming correctness and latencies based on image type. Moreover, recent studies have mainly analysed colour photographs and black-and-white line drawings leaving out image types like graphic representations that apply image features that can facilitate naming such as colour, controlled size, or texture. Aims: To shed more light on ap-propriate image types for persons with aphasia, we created graphic representations depicting nouns and verbs and compared them to photographic stimuli in a naming task including persons with aphasia (PWA) and a control group (CG). Methods & Procedures: 33 PWA and 33 age matched persons (CG) participated in the study. Naming correctness and latencies were meas-ured in two different conditions: concepts depicted as coloured photographs vs. as graphic rep-resentations. 128 pictures of linguistically controlled German-language concepts (64 nouns, 64 verbs) had to be named. The designed graphic stimuli were developed by professional designers based on photographs. The photographs were selected from stock image databases according to a defined image concept. This image concept was based on empirical findings regarding im-age features that facilitate naming (e.g., colour, texture, shading) and was applied to the selec-tion of the photographs as well as to the creation of the graphic representations. The images were presented in pseudo-randomized sequences on a tablet and all reactions of the participants were videotaped. The data from the main study was analysed using generalized linear mixed models (GLMM) and linear mixed models (LMM).
Kooperation von Logopädinnen und Logopäden in Forschung und klinischer Praxis im Aphasieprojekt «E-Inclusion»
Im Zuge der evidenzbasierten Praxis sind im Bereich der Logopädie/Sprachtherapie neben der Praxisexper - tise wissenschaftliche Erkenntnisse in die Therapie zu integrieren. Dafür wird mehr fachspezifische Forschung benötigt, die auf Unterstützung der Praxis angewiesen ist. Das Ziel des Artikels ist es, die für Logopädie-For - schung notwendige intradisziplinäre Kooperation von logopädischen Forscherinnen und Forschern sowie Prak- tikerinnen und Praktikern anhand des interdisziplinären Aphasieprojektes «E-Inclusion» der Fachhochschule Nordwestschweiz (FHNW) zu beleuchten. Dazu wird das Aphasieprojekt vorgestellt, welches vier Ziele verfolgte: (1) Auswirkungen von Dialekt und Hochdeutsch sowie (2) von Fotografien und Illustrationen auf die Bildbenenn- leistung bei u. a. Personen mit Aphasie zu untersuchen, (3) mithilfe akustisch-objektiver Sprachsignalanalysen Leistungsveränderungen der Aphasie zu ermitteln und (4) aus diesen Erkenntnissen eine Prototypen-Appli- kation zu entwickeln. Nach der Projektvorstellung gewähren logopädische Praktikerinnen und Praktiker aus Partnerinstitutionen sowie das logopädische Forschungsteam Einblick in die intradisziplinäre Kooperation. Ins- besondere die Rekrutierung der Studienteilnehmenden erforderte eine enge Zusammenarbeit. Als Resultat des Artikels zeigt sich, dass die Kooperation auch unter erschwerten Bedingungen wie zunehmender Zeitdruck im klinisch-therapeutischen Setting für beide Seiten erfolgreich, bedeutsam und bereichernd war. Daraus abgelei- tete Erkenntnisse für kooperative Projekte werden im Fazit dieses Artikels formuliert. Zukünftig können so Logo- pädinnen und Logopäden aus Forschung und Praxis, wie auch Betroffene, von der inter- und intradisziplinären Kooperation im Bereich der Logopädie bzw. in Folgeprojekten des «E-Inclusion»-Forschungsteams profitieren.
Evaluation of the Potential of Automatic Naming Latency Detection for Different Initial Phonemes during Picture Naming Task
Heading direction is significantly biased by preceding whole-body roll-orientation while lying
Background: After a prolonged static whole-body roll-tilt, a significant bias of the internal estimates of the direction of gravity has been observed when assessing the subjective visual vertical. Objective: We hypothesized that this post-tilt bias represents a more general phenomenon, broadly affecting spatial orientation and navigation. Specifically, we predicted that after the prolonged roll-tilt to either side perceived straight-ahead would also be biased. Methods: Twenty-five healthy participants were asked to rest in three different lying positions (supine, right-ear-down, and left-ear-down) for 5 min (“adaptation period”) prior to walking straight-ahead blindfolded for 2 min. Walking was recorded with the inertial measurement unit sensors attached to different body locations and with sensor shoe insoles. The raw data was segmented with a gait–event detection method. The Heading direction was determined and linear mixed-effects models were used for statistical analyses. Results: A significant bias in heading into the direction of the previous roll-tilt position was observed in the post-adaptation trials. This bias was identified in both measurement systems and decreased again over the 2-min walking period. Conclusions: The bias observed further confirms the influence of prior knowledge on spatial orientation and navigation. Specifically, it underlines the broad impact of a shifting internal estimate of direction of gravity over a range of distinct paradigms, illustrating similar decay time constants. In the broader context, the observed bias in perceived straight-ahead emphasizes that getting up in the morning after a good night's sleep is a vulnerable period, with an increased risk of falls and fall-related injuries due to non-availability of optimally tuned internal estimates of the direction of gravity and the direction of straight-ahead.
Probabilistic maps for deep brain stimulation – Impact of methodological differences
Background Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations. Objective To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters. Methods Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function. Results Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters. Conclusion The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.