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Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

ABSTRACT: In biopharmaceutical process development and manufacturing, the online measurement of biomass and derived specific turnover rates is a central task to physiologically monitor and control the process. However, hard-type sensors such as dielectric spectroscopy, broth fluorescence, or permittivity measurement harbor various disadvantages. Therefore, soft-sensors, which use measurements of the off-gas stream and substrate feed to reconcile turnover rates and provide an online estimate of the biomass formation, are smart alternatives. For the reconciliation procedure, mass and energy balances are used together with accuracy estimations of measured conversion rates, which were so far arbitrarily chosen and static over the entire process. In this contribution, we present a novel strategy within the soft-sensor framework (named adaptive soft-sensor) to propagate uncertainties from measurements to conversion rates and demonstrate the benefits: For industrially relevant conditions, hereby the error of the resulting estimated biomass formation rate and specific substrate consumption rate could be decreased by 43 and 64 %, respectively, compared to traditional soft-sensor approaches. Moreover, we present a generic workflow to determine the required raw signal accuracy to obtain predefined accuracies of soft-sensor estimations. Thereby, appropriate measurement devices and maintenance intervals can be selected. Furthermore, using this workflow, we demonstrate that the estimation accuracy of the soft-sensor can be additionally and substantially increased.

SUBMITTER: Steinwandter V

PROVIDER: S-EPMC5233751 | biostudies-other | 2017 Jan

REPOSITORIES: biostudies-other

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Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

Steinwandter Valentin V Zahel Thomas T Sagmeister Patrick P Herwig Christoph C

Analytical and bioanalytical chemistry 20160704 3

In biopharmaceutical process development and manufacturing, the online measurement of biomass and derived specific turnover rates is a central task to physiologically monitor and control the process. However, hard-type sensors such as dielectric spectroscopy, broth fluorescence, or permittivity measurement harbor various disadvantages. Therefore, soft-sensors, which use measurements of the off-gas stream and substrate feed to reconcile turnover rates and provide an online estimate of the biomass ...[more]

PMID: 27376358

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Project description:BACKGROUND:Hand hygiene is a crucial and cost-effective method to prevent health care-associated infections, and in 2009, the World Health Organization (WHO) issued guidelines to encourage and standardize hand hygiene procedures. However, a common challenge in health care settings is low adherence, leading to low handwashing quality. Recent advances in machine learning and wearable sensing have made it possible to accurately measure handwashing quality for the purposes of training, feedback, or accreditation. OBJECTIVE:We measured the accuracy of a sensor armband (Myo armband) in detecting the steps and duration of the WHO procedures for handwashing and handrubbing. METHODS:We recruited 20 participants (10 females; mean age 26.5 years, SD 3.3). In a semistructured environment, we collected armband data (acceleration, gyroscope, orientation, and surface electromyography data) and video data from each participant during 15 handrub and 15 handwash sessions. We evaluated the detection accuracy for different armband placements, sensor configurations, user-dependent vs user-independent models, and the use of bootstrapping. RESULTS:Using a single armband, the accuracy was 96% (SD 0.01) for the user-dependent model and 82% (SD 0.08) for the user-independent model. This increased when using two armbands to 97% (SD 0.01) and 91% (SD 0.04), respectively. Performance increased when the armband was placed on the forearm (user dependent: 97%, SD 0.01; and user independent: 91%, SD 0.04) and decreased when placed on the arm (user dependent: 96%, SD 0.01; and user independent: 80%, SD 0.06). In terms of bootstrapping, user-dependent models can achieve more than 80% accuracy after six training sessions and 90% with 16 sessions. Finally, we found that the combination of accelerometer and gyroscope minimizes power consumption and cost while maximizing performance. CONCLUSIONS:A sensor armband can be used to measure hand hygiene quality relatively accurately, in terms of both handwashing and handrubbing. The performance is acceptable using a single armband worn in the upper arm but can substantially improve by placing the armband on the forearm or by using two armbands.

Project description:Ascertaining the accuracy of the pedicle screw (PS) trajectories is important as PS malpositioning can cause critical complications. We aimed to determine the angle range over which estimation is unreliable; build a low-cost PS placement support system that uses an inertial measurement unit (IMU) to enable the monitoring of surgical tools and PS trajectories, and determine the situations where IMU support would be most beneficial. In PS insertion experiments, we used cadaver samples that included lumbar porcine spines. Computed tomography images obtained before and after PS insertion were viewed. Offsets between the planned and implanted PS trajectories in the freehand and IMU-assisted groups were analyzed. The PS cortical bone breaches were classified according to the Gertzbein and Robbins criteria (GRC). Added head-down tilted sample experiments were repeated wherein we expected a decreased rostro-caudal rotational accuracy of the PS according to the angle estimation ability results. Evaluation of the PS trajectory accuracy revealed no significant advantage of IMU-assisted rostro-caudal rotational accuracy versus freehand accuracy. According to the GRC, IMU assistance significantly increased the rate of clinically acceptable PS positions (RoCA) than the freehand technique. In the head-down tilted sample experiments, IMU assist provided increased accuracies with both rostro-caudal and medial rotational techniques when compared with the freehand technique. In the freehand group, RoCA was significantly decreased in samples with rostral tilting relative to that in the samples without. However, In the IMU-assisted group, no significant difference in RoCA between the samples with and without head-down tilting was observed. Even when the planned PS medial and/or rostro-caudal rotational angle was relatively large and difficult to reproduce manually, IMU-support helped maintain the PS trajectory accuracy and positioning safety. IMU assist in PS placement was more beneficial, especially for larger rostro-caudal and/or medial rotational pedicle angles.

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Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

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Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

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