Sascha Gruss | Universität Ulm (original) (raw)

Papers by Sascha Gruss

Die Anaesthesiologie, Sep 27, 2022

Mortalität und Delirinzidenz werden beim kritisch kranken Patienten durch das Analgosedierungsreg... more Mortalität und Delirinzidenz werden beim kritisch kranken Patienten durch das Analgosedierungsregime beeinflusst. Je tiefer die Sedierung, je höher die Dosis applizierter Analgetika, desto schwieriger ist die Einschätzung von Schmerz und Sedierungsgrad. Daher gewinnen apparative Messverfahren, wie die Messung der Reizschwelle des nozizeptiven Flexorenreflexes (NFRT), zunehmend an Bedeutung. Ziel der Arbeit: Ziel der vorliegenden Studie ist es, eine mögliche Assoziation zwischen der Höhe des nozizeptiven Flexorenreflexes, der Mortalität und dem Auftreten eines Delirs zu untersuchen. Material und Methodik: Durch die retrospektive Analyse eines 57 Intensivpatienten umfassenden Pilotdatensatzes der interdisziplinären operativen Intensivstation des Universitätsklinikums Ulm, erhoben zwischen November 2018 und März 2020, wurde in einem adjustierten logistischen Regressionsmodell eine mögliche Assoziation zwischen NFRT, Mortalität und Delirinzidenz berechnet. Je nach Cutoff -Wert ergeben sich Reizschwellenkorridore mit folgenden Vergleichspaaren: < 20 mA vs. 20-40 mA/20-50 mA/20-60 mA,> 40 mA vs. 20-40 mA, > 50 mA vs. 20-50 mA, > 60 mA vs. 20-60 mA. Die Ergebnisdarstellung erfolgt als Odds Ratios, bereinigt um Alter, Geschlecht, Größe, TISS-28, SAPS II, RASS, BPS und die verwendeten Analgetika. Die Schmerzerfassung erfolgte in der untersuchten Gruppe standardisiert mittels der Behavioral Pain Scale sowie ergänzend durch die NFRT-Messung. Ergebnisse: Es konnte eine statistisch nicht signifikante Tendenz zu einer Mortalitätszunahme bei einer NFRT > 50 mA gegenüber dem Reizschwellenkorridor von 20-50 mA ermittelt werden (OR 3.3, KI: 0,89-12.43, p = 0,07). Eine Tendenz zu einer Reduktion der Delirhäufigkeit trat bei einer NFRT < 20 mA gegenüber einem Reizschwellenkorridor von 20-40 mA auf (OR 0.40, KI: 0,18-0,92, p = 0,03). Diskussion: Anhand der Höhe der NFRT kann zum aktuellen Zeitpunkt keine Empfehlung zur Anpassung des verwendeten Analgosedierungsregimes beim kritisch kranken, nichtmitteilungsfähigen Intensivpatienten gegeben werden. Die Beobachtung einer Tendenz hin zu einer Zunahme der Mortalität bei hohen Reizschwellen bzw. einer Reduktion des Auftretens eines Delirs bei niedrigen Reizschwellen muss in standardisierten Studien überprüft werden.

IEEE Conference Proceedings, 2016

Research Square (Research Square), Feb 16, 2021

Background Pain detection and treatment is a major challenge in the care of critically ill patien... more Background Pain detection and treatment is a major challenge in the care of critically ill patients. However, in addition to the risk of analgesic undersupply, there is also the risk of overanalgesia. In the perioperative context, the measurement of the nociceptive exion re ex threshold has become established for measuring the level of analgesia. To date, however, it is unclear whether measurement of NFRT can be usefully applied to noncommunicating, ventilated, and analgosedated ICU patients. Therefore, the aim of the present study was to investigate whether NFRT measurement correlates with the Behavioral Pain Scale (BPS) in critically ill, analgosedated, and mechanically ventilated patients and whether it can also detect possible overanalgesia. Methods In this prospective, observational, single-center study, 114 patients were included. All patients were admitted to the surgical Intensive Care Unit of the University hospital Ulm, Germany. First measurements of the NFRT and the Behavioral Pain Scale (BPS) were conducted within 12 hours after admission. In the further observation period, a structured pain assessment was performed at least twice daily until extubation (Group A: BPS + NFRT, Group B: BPS). Univariate analysis was performed to evaluate possible associations between NFRT measurement and baseline characteristics. Furthermore, mixed linear regression modeling was used to evaluate possible effects of administered analgesics or sedatives on NFRT. Results NFRT correlates negatively with the Behavioral Pain Scale. NFRT was almost twice as high in patients with a RASS of-5 compared with patients with a RASS ≥-4 (RASS-5-NFRT: 59.40 vs. RASS-4-NFRT: 29.00, p < 0.001). By means of NFRT measurement, potential overanalgesia could not be detected.

Zeitschrift Fur Gastroenterologie, Aug 13, 2019

Life

This study focuses on improving healthcare quality by introducing an automated system that contin... more This study focuses on improving healthcare quality by introducing an automated system that continuously monitors patient pain intensity. The system analyzes the Electrodermal Activity (EDA) sensor modality modality, compares the results obtained from both EDA and facial expressions modalities, and late fuses EDA and facial expressions modalities. This work extends our previous studies of pain intensity monitoring via an expanded analysis of the two informative methods. The EDA sensor modality and facial expression analysis play a prominent role in pain recognition; the extracted features reflect the patient’s responses to different pain levels. Three different approaches were applied: Random Forest (RF) baseline methods, Long-Short Term Memory Network (LSTM), and LSTM with the sample-weighting method (LSTM-SW). Evaluation metrics included Micro average F1-score for classification and Mean Squared Error (MSE) and intraclass correlation coefficient (ICC [3, 1]) for both classification...

Journal of Visual Communication and Image Representation

Frontiers in Medicine

BackgroundIn the clinical context, the assessment of pain in patients with inadequate communicati... more BackgroundIn the clinical context, the assessment of pain in patients with inadequate communication skills is standardly performed externally by trained medical staff. Automated pain recognition (APR) could make a significant contribution here. Hereby, pain responses are captured using mainly video cams and biosignal sensors. Primary, the automated monitoring of pain during the onset of analgesic sedation has the highest relevance in intensive care medicine. In this context, facial electromyography (EMG) represents an alternative to recording facial expressions via video in terms of data security. In the present study, specific physiological signals were analyzed to determine, whether a distinction can be made between pre-and post-analgesic administration in a postoperative setting. Explicitly, the significance of the facial EMG regarding the operationalization of the effect of analgesia was tested.MethodsN = 38 patients scheduled for surgical intervention where prospectively recrui...

Background: The clinically used methods of pain diagnosis do not allow for objective and robust m... more Background: The clinically used methods of pain diagnosis do not allow for objective and robust measurement, and physicians must rely on the patient’s report on the pain sensation. Verbal scales, visual analog scales (VAS) or numeric rating scales (NRS) count among the most common tools, which are restricted to patients with normal mental abilities. There also exist instruments for pain assessment in people with verbal and / or cognitive impairments and instruments for pain assessment in people who are sedated and automated ventilated. However, all these diagnostic methods either have limited reliability and validity or are very time-consuming. In contrast, biopotentials can be automatically analyzed with machine learning algorithms to provide a surrogate measure of pain intensity. Methods: In this context, we created a database of biopotentials to advance an automated pain recognition system, determine its theoretical testing quality, and optimize its performance. Eighty-five participants were subjected to painful heat stimuli (baseline, pain threshold, two intermediate thresholds, and pain tolerance threshold) under controlled conditions and the signals of electromyography, skin conductance level, and electrocardiography were collected. A total of 159 features were extracted from the mathematical groupings of amplitude, frequency, stationarity, entropy, linearity, variability, and similarity. Results: We achieved classification rates of 90.94% for baseline vs. pain tolerance threshold and 79.29% for baseline vs. pain threshold. The most selected pain features stemmed from the amplitude and similarity group and were derived from facial electromyography. Conclusion: The machine learning measurement of pain in patients could provide valuable information for a clinical team and thus support the treatment assessment

The fact that training classification algorithms in a within-subject design is inferior to traini... more The fact that training classification algorithms in a within-subject design is inferior to training on between subject data is discussed for an electrophysiological data set. Event-related potentials were recorded from 18 subjects, emotionally stimulated by a series of 18 negative, 18 positive and 18 neutral pictures of the International Affective Picture System. In addition to traditional averaging and group comparison of event related potentials, electroencephalographical data have been intra-and inter-individually classified using a Support Vector Machine for emotional conditions. Support vector machine classifications based upon intraindividual data showed significantly higher classification rates [F(19.498),p<.001] than global ones. An effect size was calculated (d = 1.47) and the origin of this effect is discussed within the context of individual response specificities. This study clearly shows that classification accuracy can be boosted by using individual specific settings.

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first ha... more OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

2017 International Conference on Companion Technology (ICCT), 2017

In this work, different cognitive load situations are examined and classified in the context of a... more In this work, different cognitive load situations are examined and classified in the context of a Human Computer Interaction (HCI) scenario. Machine learning methods were used to detect three cognitive load states (overload, underload, normal load) with the help of five different psychophysiological signals (ECG, EMG, Respiration, GSR, Temperature). At first it is shown, that the three regarded states can be clearly distinguished in the Valence-Arousal-Dominance space (VAD). After this comparisons between a 10-fold-valdidation and a batch-validation as well as three different classifiers (k-Nearest-Neighbour, Naive Bayes, Random Forest) are accomplished. At last the influence of gender in contrast to an overall analysis is shown.

IEEE Transactions on Affective Computing, 2019

The subjective nature of pain makes it a very challenging phenomenon to assess. Most of the curre... more The subjective nature of pain makes it a very challenging phenomenon to assess. Most of the current pain assessment approaches rely on an individual’s ability to recognise and report an observed pain episode. However, pain perception and expression are affected by numerous factors ranging from personality traits to physical and psychological health state. Hence, several approaches have been proposed for the automatic recognition of pain intensity, based on measurable physiological and audiovisual parameters. In the current paper, an assessment of several fusion architectures for the development of a multi-modal pain intensity classification system is performed. The contribution of the presented work is two-fold: (1) 3 distinctive modalities consisting of audio, video and physiological channels are assessed and combined for the classification of several levels of pain elicitation. (2) An extensive assessment of several fusion strategies is carried out in order to design a classification architecture that improves the performance of the pain recognition system. The assessment is based on the <italic>SenseEmotion Database</italic> and experimental validation demonstrates the relevance of the multi-modal classification approach, which achieves classification rates of respectively <inline-formula><tex-math notation="LaTeX">$83.39\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>83</mml:mn><mml:mo>.</mml:mo><mml:mn>39</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="thiam-ieq1-2892090.gif"/></alternatives></inline-formula>, <inline-formula><tex-math notation="LaTeX">$59.53\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>59</mml:mn><mml:mo>.</mml:mo><mml:mn>53</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="thiam-ieq2-2892090.gif"/></alternatives></inline-formula> and <inline-formula><tex-math notation="LaTeX">$43.89\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>43</mml:mn><mml:mo>.</mml:mo><mml:mn>89</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="thiam-ieq3-2892090.gif"/></alternatives></inline-formula> in a 2-class, 3-class and 4-class pain intensity classification task.

2016 IEEE Symposium Series on Computational Intelligence (SSCI), 2016