Rotator cuff repair: an analysis of failure mechanisms and predictors of structural and clinical repair outcomes

Post-operative Re-Rupturen stellen die wohl grösste Herausforderung bei der chirurgischen Versorgung von Rotatorenmanschettenrupturen dar. Inwieweit diese Re-Defekte klinische Relevanz haben, wird derzeit kontrovers diskutiert. Diese Dissertation untersucht mögliche Mechanismen, welche zur Entstehung von Re-Defekten führen. Um die klinische Relevanz dieser Mechanismen zu bewerten, das Verhältnis von strukuturellem und klinischem Operationsergebnis zu untersuchen und mögliche Ergebnisprediktoren zu identifzieren, wurde eine Meta-Analyse von 31 klinischen Studien durchgeführt. Die Daten dieser Analyse bewiesen, dass auch in Patienten mit post-operativer Re-Ruptur, eine signifikante Verbesserung klinischer Symptome erzielt wird. Jedoch zeigte der Vergleich der Daten re-rupturierter und intakter Sehnen, einen statistisch signifikanten Unterschied zu Gunsten post-operativ intakter Manschetten. Hinsichtlich predominanter Fehlermechanismen konnte die Analyse klinischer Studien nur begrenzt Aufschluss geben. Nach Zusammenfassung der klinischen Daten, sowie den Ergebnissen einer generellen Literaturrecherche, konnten bestimmte Problemzonen heutiger Behandlungstechniken identifiziert werden. Abschliessend wird ein ovines Manschettenmodel präsentiert, welches in erster Linie die Untersuchung einer post-operativen Lückenbildung zwischen der re-inserierten Sehne und ihrem knöchernen Ursprung ermöglicht. Zudem erlaubt es die Untersuchung genereller Aspekte der Heilung reparierter Manschetten. Post-operative re-tearing represents a major challenge in the surgical treatment of rotator cuff tears. Whether or not re-torn cuffs inevitably cause inferior clinical outcomes is temporarily a subject of controversial debate. This thesis investigates the occurrence of rotator cuff re-tearing by analyzing the repair components of current surgical concepts and discussing potential failure mechanisms. In order to evaluate the clinical relevance of these mechanisms, investigate the relation of structural repair failure and clinical outcome and furthermore identify predictors of structural and clinical outcomes, a meta-analysis of 31 studies (3611 shoulders in total) was performed. The data showed significant relief of clinical symptoms and an increase in shoulder function in both, patients with intact repairs and those showing cuff re-tears. However, it also confirmed a correlation between re-torn cuffs and generally lower clinical results. The meta-analysis of patient, surgical, imaging and clinical follow-up data could only very limitedly provide information about the underlying mechanisms of failure. When synthesizing results from the clinical study meta-analysis and general research including animal and ex-vivo studies, several hot spots in current concepts were identified. Finally, an ovine model is presented that allows further investigation of repair site gap formation and assessment of general aspects and timing of rotator cuff healing

Identifying the BLE Advertising Channel for Reliable Distance Estimation on Smartphones

Estimating the distance between two smartphones plays an important role in a host of applications. For this purpose, smartphones emit and scan for Bluetooth Low Energy (BLE) signals. When a device is detected, the distance is estimated by evaluating the received strength of these signals. The main insight that is exploited for distance estimation is that the attenuation of a signal increases with the distance along which it has traveled. However, besides distance, there are multiple additional factors that impact the attenuation and hence disturb the distance estimation procedure. Among them, frequency-selective hardware and signal propagation belong to the most significant ones. For example, a BLE device transmits packets on three different frequencies (channels), while the transmit power and the receiver sensitivity depend on the frequency. As a result, the received signal strength varies for each channel, even when the distance remains constant. However, the information on which wireless channel a packet has been received is not made available to a smartphone. Hence, this error cannot be compensated, e.g. by calibration. In this paper, we for the first time provide a solution to detect the wireless channel on which a packet has been received by a smartphone application. We experimentally evaluate our proposed technique on multiple different smartphone models. Our results help to make distance estimation on smartphones more robust and accurate

Practical identity recognition using WiFi's Channel State Information

Identity recognition is increasingly used to control access to sensitive data, restricted areas in industrial, healthcare, and defense settings, as well as in consumer electronics. To this end, existing approaches are typically based on collecting and analyzing biometric data and imply severe privacy con-cerns. Particularly when cameras are involved, users might even reject or dismiss an identity recognition system. Furthermore, iris or fingerprint scanners, cameras, microphones, etc., imply installation and maintenance costs and require the user's active participation in the recognition procedure. This paper proposes a non-intrusive identity recognition system based on analyzing WiFi's Channel State Information (CSI). We show that CSI data attenuated by a person's body and typical movements allows for a reliable identification - even in a sitting posture. We further propose a lightweight deep learning algorithm trained using CSI data, which we implemented and evaluated on an embedded platform (i.e., a Raspberry Pi 4B). Our results obtained using real-world experiments suggest a high accuracy in recognizing people's identity, with a specificity of 98% and a sensitivity of 99%, while requiring a low training effort and negligible cost

On recent developments for high-speed atomic force microscopy

The atomic force microscope (AFM) is limited in imaging speed by the bandwidth and dynamic behavior of the actuators and mechanical parts. For high-speed imaging all AFM components have to be optimized in performance. Here, we present improvements of the force sensor, the scanner, the controller, and the data acquisition system. By combining all these improvements, the next generation AFMs will enable imaging speeds more than two orders of magnitude faster than current commercial AFM systems