Audio-video Synchronization with Arbitrary, Non-periodic Video Sources

The latency between audio and video streams of a device is usually measured using stock test videos. Although the use of stock test videos eases analysis, the test video differs materially from real-world videos, which tend to be far more diverse in content and encoding schemes, resulting in laborious experimental setup and inaccurate synchronization. This disclosure describes techniques to measure the latency between the audio and video streams of a given device using arbitrary, real-world, audio-visual footage (test video). Characteristic video and audio frames and their differences in timestamps (characteristic durations) are identified within the test video. The test video is played by the device-under-test while being recorded by a high-precision video camera. Characteristic durations of the recorded footage are determined. The differences in characteristic durations between the test and the recorded videos are statistically analyzed to determine the AV asynchrony of the device-under-test

Strength is in numbers: Can concordant artificial listeners improve prediction of emotion from speech?

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present 'intelligent personal assistants', and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants' emotional state, selective/differential data collection based on emotional content, etc.)

Bewegungssynchronie zwischen Patienten mit Sozialer Angststörung und ihren Psychotherapeuten: Testung, Weiterentwicklung und Anwendung linearer zeitreihenanalytischer Verfahren

Bewegungssynchronie zwischen Patient und Psychotherapeut beschreibt das Aufeinander-Bezug-nehmen von deren Bewegungen und ist mit Outcome-Maßen der Psychotherapie assoziiert. Diese Zusammenhänge wurden meist in störungsheterogenen Stichproben verschiedener Behandlungskonzepte gefunden. Der Einfluss der Störung und des Behandlungskonzeptes kann nicht ausgeschlossen werden. Die Untersuchungen wurden mittels zeitreihenanalytischen Methoden durchgeführt. Aktuell fehlt eine umfassende Prüfung der Methoden anhand verschiedener Validitätskriterien. Innerhalb dieser Arbeit wurde die Bewegungssynchronie zu verschiedenen Zeitpunkten dreier verschiedener Kurzzeit-/Langzeittherapien (manualisierte kognitive Verhaltenstherapie, manualisierte psychodynamisch-orientierte Therapie und naturalistische kognitive Verhaltenstherapie) von Patienten mit Sozialer Angststörung in Zusammenhang zu verschiedenen Outcome-Maßen (Therapieabbruch, Symptomatik, Bindung) untersucht. Dabei wurde die Bewegungssynchronie automatisiert aus Videosequenzen mittels Motion Energy Analysis und Windowed Cross-Lagged Correlation gewonnen. Bei den Validitätsuntersuchungen stellte sich heraus, dass verschiedene Synchronie-Maße kein eindimensionales Konstrukt sondern verschiedene Facetten von Synchronie messen: die Häufigkeit der Synchronie, die Stärke der Synchronie in Synchronisationsintervallen und die Stärke der Synchronie in der Gesamtinteraktion, die auch unterschiedlich mit Outcome-Maßen assoziiert waren. Die Untersuchung der Synchronie-Outcome-Assoziation zeigte einen Zusammenhang von höherer Synchronie zu Beginn der Therapie mit einer geringeren Abbruchrate, reduzierten interpersonellen Problemen und Bindungsängsten des Patienten zum Ende der Therapie sowie eine verbesserte therapeutische Allianz. Die Ergebnisse verdeutlichen, dass Bewegungssynchronie einen differentiellen Effekt in Abhängigkeit des Outcomes, Zeitgebers, Therapieverfahrens, Inhalt der Sitzungen und der verwendeten Methodik hat

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

NOVEL GRAPHICAL MODEL AND NEURAL NETWORK FRAMEWORKS FOR AUTOMATED SEIZURE DETECTION, TRACKING, AND LOCALIZATION IN FOCAL EPILEPSY

Epilepsy is a heterogenous neurological disorder characterized by recurring and unprovoked seizures. It is estimated that 60% of epilepsy patients suffer from focal epilepsy, where seizures originate from one or more discrete locations within the brain. After onset, focal seizure activity spreads, involving more regions in the cortex. Diagnosis and therapeutic planning for patients with focal epilepsy crucially depends on being able to detect epileptic activity as it starts and localize its origin. Due to the subtlety of seizure activity and the complex spatio-temporal propagation patterns of seizure activity, detection and localization of seizure by visual inspection is time-consuming and must be done by highly trained neurologists. In this thesis, we detail modeling approaches to identify and capture the spatio-temporal ictal propagation of focal epileptic seizures. Through novel multi-scale frameworks, information fusion between signal paths, and hybrid architectures, models that capture the underlying seizure propagation phenomena are developed. The first half relies on graphical modeling approaches to detect seizures and track their activity through the space of EEG electrodes. A coupled hidden Markov model approach to seizure propagation is described. This model is subsequently improved through the addition of convolutional neural network based likelihood functions, removing the reliance on hand designed feature extraction. Through the inclusion of a hierarchical switching chain and localization variables, the model is revised to capture multi-scale seizure onset and spreading information. In the second half of this thesis, end-to-end neural network architectures for seizure detection and localization are developed. First, combination convolutional and recurrent neural networks are used to identify seizure activity at the level of individual EEG channels. Through novel aggregation, the network is trained to recognize seizure activity, track its evolution, and coarsely localize seizure onset from lower resolution labels. Next, a multi-scale network capable of analyzing the global and electrode level signals is developed for challenging task of end-to-end seizure localization. Onset location maps are defined for each patient and an ensemble of weakly supervised loss functions are used in a multi-task learning framework to train the architecture

Muscle activation patterns in shoulder impingement patients

Introduction: Shoulder impingement is one of the most common presentations of shoulder joint problems 1. It appears to be caused by a reduction in the sub-acromial space as the humerus abducts between 60o -120o – the 'painful arc'. Structures between the humeral head and the acromion are thus pinched causing pain and further pathology 2. Shoulder muscle activity can influence this joint space but it is unclear whether this is a cause or effect in impingement patients. This study aimed to observe muscle activation patterns in normal and impingement shoulder patients and determine if there were any significant differences. Method: 19 adult subjects were asked to perform shoulder abduction in their symptomatic arm and non-symptomatic. 10 of these subjects (age 47.9 ± 11.2) were screened for shoulder impingement, and 9 subjects (age 38.9 ± 14.3) had no history of shoulder pathology. Surface EMG was used to collect data for 6 shoulder muscles (Upper, middle and lower trapezius, serratus anterior, infraspinatus, middle deltoids) which was then filtered and fully rectified. Subjects performed 3 smooth unilateral abduction movements at a cadence of 16 beats of a metronome set at 60bpm, and the mean of their results was recorded. T-tests were used to indicate any statistical significance in the data sets. Significance was set at P<0.05. Results: There was a significant difference in muscle activation with serratus anterior in particular showing a very low level of activation throughout the range when compared to normal shoulder activation patterns (<30%). Middle deltoid recruitment was significantly reduced between 60-90o in the impingement group (30:58%).Trends were noted in other muscles with upper trapezius and infraspinatus activating more rapidly and erratically (63:25%; 60:27% respectively), and lower trapezius with less recruitment (13:30%) in the patient group, although these did not quite reach significance. Conclusion: There appears to be some interesting alterations in muscle recruitment patterns in impingement shoulder patients when compared against their own unaffected shoulders and the control group. In particular changes in scapula control (serratus anterior and trapezius) and lateral rotation (infraspinatus), which have direct influence on the sub-acromial space, should be noted. It is still not clear whether these alterations are causative or reactionary, but this finding gives a clear indication to the importance of addressing muscle reeducation as part of a rehabilitation programme in shoulder impingement patients