Long-term functional and clinical outcome of combined targeted muscle reinnervation and osseointegration for functional bionic reconstruction in transhumeral amputees: a case series.

OBJECTIVE: To describe and evaluate the combination of osseointegration and nerve transfers in 3 transhumeral amputees. DESIGN: Case series. PATIENTS: Three male patients with a unilateral traumatic transhumeral amputation. METHODS: Patients received a combination of osseointegration and targeted muscle reinnervation surgery. Rehabilitation included graded weight training, range of motion exercises, biofeedback, table-top prosthesis training, and controlling the actual device. The impairment in daily life, health-related quality of life, and pain before and after the intervention was evaluated in these patients. Their shoulder range of motion, prosthesis embodiment, and function were documented at a 2- to 5-year follow-up. RESULTS: All 3 patients attended rehabilitation and used their myoelectric prosthesis on a daily basis. Two patients had full shoulder range of motion with the prosthesis, while the other patient had 55° of abduction and 45° of anteversion. They became more independent in their daily life activities after the intervention and incorporated their prosthesis into their body scheme to a high extent. CONCLUSION: These results indicate that patients can benefit from the combined procedure. However, the patients' perspective, risks of the surgical procedures, and the relatively long rehabilitation procedure need to be incorporated in the decision-making.

Instrument for tensile testing of individual collagen fibrils with facile sample coupling and uncoupling.

Collagen is the major structural protein in human bodies constituting about 30% of the entire protein mass. Through a self-assembly process, triple helical collagen molecules assemble into high aspect-ratio fibers of tens to hundreds of nanometer diameter, known as collagen fibrils (CFs). In the last decade, several methods for tensile testing these CFs emerged. However, these methods are either overly time-consuming or offer low data acquisition bandwidth, rendering dynamic investigation of tensile properties impossible. Here, we describe a novel instrument for tensile testing of individual CFs. CFs are furnished with magnetic beads using a custom magnetic tweezer. Subsequently, CFs are lifted by magnetic force, allowing them to be picked-up by a microgripper structure, which is mounted on a cantilever-based interferometric force probe. A piezo-lever actuator is used to apply tensile displacements and to perform tensile tests of tethered CFs, after alignment. Once the mechanical tests are finished, CFs are removed from the microgripper by application of a magnetic field. Our novel instrument enables tensile tests with at least 25-fold increased throughput compared to tensile testing with an atomic force microscope while achieving force resolution (p-p) of 10 nN at a strain resolution better than 0.1%.

A data mining approach to reduce the false alarm rate of patient monitors.

Patient monitors in intensive care units trigger alarms if the state of the patient deteriorates or if there is a technical problem, e.g. loose sensors. Monitoring systems have a high sensitivity in order to detect relevant changes in the patient state. However, multiple studies revealed a high rate of either false or clinically not relevant alarms. It was found that the high rate of false alarms has a negative impact on both patients and staff. In this study we apply data mining methods to reduce the false alarm rate of monitoring systems. We follow a multi-parameter approach where multiple signals of a monitoring system are used to classify given alarm situations. In particular we focus on five alarm types and let our system decide whether the triggered alarm is clinically relevant or can be considered as a false alarm. Several classification algorithms (Naive Bayes, Decision Trees, SVM, kNN and Multi-Layer Perceptron) were evaluated. For training and test sets a subset of the freely available MIMIC II database was used. Alarm-specific classification accuracy was between 78.56% and 98.84%. Suppression rates for false alarms were between 75.24% and 99.23%. Classification results strongly depend on available training data, which is still limited in the intensive care domain. However, this study shows that data mining methods are useful and applicable for alarm classification.

A comparative study on extra-corporal circulation control.

Hydraulic models of the human circulatory system allow simulation of hemodynamics in a standardized setting. In this work we use such a model to compare concurrent control strategies for extra-corporal circulation control. Patients suffering from cardio-vascular diseases under extra-corporal circulation can benefit from an automated regulation. The control task is to keep either the pump flow or the pressure in the cardio-vascular system at a constant target value, despite any parameter variations or external perturbations. We implement four control strategies that seem favorable for our task: a Proportional-Integral Controller, a H(∞)-Controller, a PI-Fuzzy Controller and a Model Reference Adaptive Controller. The methods are compared quantitatively and their advantages and drawbacks are discussed.