Abstract: Identifying the direction of emotional influence in a dyadic dialogue is of increasing interest in the psychological sciences with applications in psychotherapy, analysis of political interactions, or interpersonal conflict behavior. Facial expressions are widely described as being automatic and thus hard to be overtly influenced. As such, they are a perfect measure for a better understanding of unintentional behavior cues about socio-emotional cognitive processes. With this view, this study is concerned with the analysis of the direction of emotional influence in dyadic dialogues based on facial expressions only. We exploit computer vision capabilities along with causal inference theory for quantitative verification of hypotheses on the direction of emotional influence, i.e., cause-effect relationships, in dyadic dialogues. We address two main issues. First, in a dyadic dialogue, emotional influence occurs over transient time intervals and with intensity and direction that are variant over time. To this end, we propose a relevant interval selection approach that we use prior to causal inference to identify those transient intervals where causal inference should be applied. Second, we propose to use fine-grained facial expressions that are present when strong distinct facial emotions are not visible. To specify the direction of influence, we apply the concept of Granger causality to the time-series of facial expressions over selected relevant intervals. We tested our approach on newly, experimentally obtained data. Based on quantitative verification of hypotheses on the direction of emotional influence, we were able to show that the proposed approach is promising to reveal the cause-effect pattern in various instructed interaction conditions.

Abstract: The human face has a high potential for biometric identification due to its many individual traits. At the same time, such identification is vulnerable to biometric copies. These presentation attacks pose a great challenge in unsupervised authentication settings. As a countermeasure, we propose a method that automatically analyzes the plausibility of facial behavior based on a sequence of 3D face scans. A compact feature representation measures facial behavior using the temporal curvature change. Finally, we train our method only on genuine faces in an anomaly detection scenario. Our method can detect presentation attacks using elastic 3D masks, bent photographs with eye holes, and monitor replay-attacks. For evaluation, we recorded a challenging database containing such cases using a high-quality 3D sensor. It features 109 4D face scans including eleven different types of presentation attacks. We achieve error rates of 11% and 6% for APCER and BPCER, respectively.

Abstract: Human nonverbal emotional communication in dyadic dialogs is a process of mutual influence and adaptation. Identifying the direction of influence, or cause-effect relation between participants, is a challenging task due to two main obstacles. First, distinct emotions might not be clearly visible. Second, participants cause-effect relation is transient and variant over time. In this paper, we address these difficulties by using facial expressions that can be present even when strong distinct facial emotions are not visible. We also propose to apply a relevant interval selection approach prior to causal inference to identify those transient intervals where adaptation process occurs. To identify the direction of influence, we apply the concept of Granger causality to the time series of facial expressions on the set of relevant intervals. We tested our approach on synthetic data and then applied it to newly, experimentally obtained data. Here, we were able to show that a more sensitive facial expression detection algorithm and a relevant interval detection approach is most promising to reveal the cause-effect pattern for dyadic communication in various instructed interaction conditions.

Abstract: Fragestellung Anne Heinzl et al. fanden bei der standardisierten Sonographie der mimischen Muskulatur von 38 Patienten mit Parkinson Syndrom signifikant verminderte Muskelquerschnittsflächen und Muskeldynamik im Vergleich zu geschlechtsspezifischen Referenzwerten. Bei Frauen zeigte sich eine 33,12%, bei Männern eine 36,67 % verminderte Kontraktilität gegenüber den gesunden Patienten, was eine genaue Quantifizierung der Bradykinese erlaubte (Heinzl 2018). Darauf aufbauend sind jetzt longitudinale Erhebungen mittels dynamischer Sonografie und optischen 3D-Videos an Parkinson Patienten geplant. Material und Methode Erhebung hochfrequenter Ultraschall-Videos und optischer 3D-Videos von je 3 Willkürkontraktionen im medikamentösen Off und On-State bei Patienten mit M. Parkinson. Erfassung der motorischen Beeinträchtigung mittels MDS Unified Parkinson Disease Rating Scale (MDS-UPDRS) III. Ergebnisse Der klinische Schwergradscore (MDS UPDRS III) soll mit den Veränderungen der Muskeldynamik, die sonographisch als auch optisch quantifiziert werden, korreliert werden. Wir erhoffen damit Rückschlüsse auf die Schwere der Erkrankung, aber auch auf die Wirksamkeit der medikamentösen Therapie ziehen zu können. Das ursprünglich für die Diagnostik von Fazialisparesen erstelle Ultraschall-Protokoll soll für diese neue Anwendung optimiert werden. Um einen schnellen und routinemäigen Einsatz des Ultraschalls zu ermöglichen, sollen besonders geeignete Muskeln identifiziert werden. Zudem soll geklärt werden, ob auch die optischen 3D-Videos bereits ähnliche Aussagen erlauben. Schlussfolgerung Wir hoffen mittels hochfrequenter Sonographie, aber auch mit 3D-Videos erstmals die Veränderungen der Muskeldynamik von Patienten mit M. Parkinson intra-individuell quantifizieren zu können. Damit wäre das Hauptsymptom Bradykinese auch empirisch nutzbar und quantifizierbar. Dies könnte ein Werkzeug für Studien und für die empirische Optimierung der Medikation sein.

Abstract: 5 patients with facial paralysis received a home-based electrostimulation (ES) with charge-balanced biphasic triangular impulses 3x5min twice a day. Before the first ES, and every 4 weeks during the ES, all patients underwent regular needle electromyography (EMG), ultrasound and 3D-video measurements. Additionally, stimulation settings, patients? home-stimulation diaries and parameters were recorded. No patient reported relevant adverse events linked to ES. Training with optimized electrode positioning was associated with stable and specific zygomaticus muscle activation, accompanied by a reduction of the necessary minimum pulse duration from 250 to 70ms per phase within 16 weeks. Even before reinnervation, objective 3D-videos, sonography, MRI, and patient-related parameters (FDI, FaCE) improved significantly compared to the pre-stimulation situation. Preliminary results suggest that ES home-based training is beneficial for patients with denervated facial muscles in reducing muscle atrophy, maintaining muscle function and improving facial symmetry. A lack of relevant adverse events shows that such ES is safe. The patients showed excellent compliance with the protocol and rated the stimulation easy and effective.