Acoustic Monitoring and Localization for Social Care

Stefan Goetze,Jens Schroder,Stephan Gerlach,Danilo Hollosi,Jens-E. Appell,Frank Wallhoff 한국정보과학회 2012 Journal of Computing Science and Engineering Vol.6 No.1

Increase in the number of older people due to demographic changes poses great challenges to the social healthcare systems both in the Western and as well as in the Eastern countries. Support for older people by formal care givers leads to enormous temporal and personal efforts. Therefore, one of the most important goals is to increase the efficiency and effectiveness of today’s care. This can be achieved by the use of assistive technologies. These technologies are able to increase the safety of patients or to reduce the time needed for tasks that do not relate to direct interaction between the care giver and the patient. Motivated by this goal, this contribution focuses on applications of acoustic technologies to support users and care givers in ambient assisted living (AAL) scenarios. Acoustic sensors are small, unobtrusive and can be added to already existing care or living environments easily. The information gathered by the acoustic sensors can be analyzed to calculate the position of the user by localization and the context by detection and classification of acoustic events in the captured acoustic signal. By doing this, possibly dangerous situations like falls, screams or an increased amount of coughs can be detected and appropriate actions can be initialized by an intelligent autonomous system for the acoustic monitoring of older persons. The proposed system is able to reduce the false alarm rate compared to other existing and commercially available approaches that basically rely only on the acoustic level. This is due to the fact that it explicitly distinguishes between the various acoustic events and provides information on the type of emergency that has taken place. Furthermore, the position of the acoustic event can be determined as contextual information by the system that uses only the acoustic signal. By this, the position of the user is known even if she or he does not wear a localization device such as a radio-frequency identification (RFID) tag.

Acoustic Monitoring and Localization for Social Care

Goetze, Stefan,Schroder, Jens,Gerlach, Stephan,Hollosi, Danilo,Appell, Jens-E.,Wallhoff, Frank Korean Institute of Information Scientists and Eng 2012 Journal of Computing Science and Engineering Vol.6 No.1

Increase in the number of older people due to demographic changes poses great challenges to the social healthcare systems both in the Western and as well as in the Eastern countries. Support for older people by formal care givers leads to enormous temporal and personal efforts. Therefore, one of the most important goals is to increase the efficiency and effectiveness of today's care. This can be achieved by the use of assistive technologies. These technologies are able to increase the safety of patients or to reduce the time needed for tasks that do not relate to direct interaction between the care giver and the patient. Motivated by this goal, this contribution focuses on applications of acoustic technologies to support users and care givers in ambient assisted living (AAL) scenarios. Acoustic sensors are small, unobtrusive and can be added to already existing care or living environments easily. The information gathered by the acoustic sensors can be analyzed to calculate the position of the user by localization and the context by detection and classification of acoustic events in the captured acoustic signal. By doing this, possibly dangerous situations like falls, screams or an increased amount of coughs can be detected and appropriate actions can be initialized by an intelligent autonomous system for the acoustic monitoring of older persons. The proposed system is able to reduce the false alarm rate compared to other existing and commercially available approaches that basically rely only on the acoustic level. This is due to the fact that it explicitly distinguishes between the various acoustic events and provides information on the type of emergency that has taken place. Furthermore, the position of the acoustic event can be determined as contextual information by the system that uses only the acoustic signal. By this, the position of the user is known even if she or he does not wear a localization device such as a radio-frequency identification (RFID) tag.

Space‑Vector‑Based Hybrid PWM for Zero‑Sequence‑Circulating‑Current RMS and Common Mode Voltage Reduction in Two Parallel Interleaved Two‑Level Converters

Zhiyong Zeng,Zhongxi Li,Stefan M. Goetz 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.3

This paper aims at reducing the root mean square (RMS) values of the zero-sequence circulating current (ZSCC). The analysis reveals that the ZSCC is determined by the duty ratios of the medium voltage vector and zero vector. Whereas the reference voltage fxes the duty ratio of the medium vector, the duty ratio of the zero-voltage vector depends on the distribution of the small and larger vectors, which can be used to optimize the ZSCC. As such, we propose a generalized PWM architecture, where the distribution of the active vectors is parameterized by a coefcient k. Based on this, we derive regions for k that attain the same minimal ZSCC peak. Within these regions, we further optimize k to minimize the ZSCC RMS. Depending on the reference voltage, the method selects diferent coefcient k for the ZSCC RMS optimizations. The proposed modulation strategy is therefore a HBSVM due to its adaptive feature in the distribution of the active vectors. The proposed HBSVM uniformly applies to the entire vector plane and is computationally afordable for mainstream microcontrollers. Finally, the experimental results validate the merits of the proposed method.

A Control Scheme to Reduce the Current Load of Integrated Batteries in Cascaded Multilevel Converters

Christian Korte,Eduard Specht,Stefan M. Goetz,Marc Hiller 전력전자학회 2019 ICPE(ISPE)논문집 Vol.2019 No.5

While battery-integrated modular multilevel converters are a promising alternative to conventional inverters in applications such as automobiles, they often cause significant second-harmonic pulsating currents in the batteries, increasing their degradation rate and the system losses. In this paper, we propose a control scheme for the Modular Multilevel Series Parallel Converter (MMSPC) that reduces the pulsating current seen by the batteries. A harmonic voltage is injected into the controller output voltage, allowing the converter to significantly reduce the low frequency current pulsations by switching modules in parallel more often. This is combined with a simple balancing algorithm to determine the upcoming switching states. We have shown that–without the need of additional hardware–the second-harmonic pulsation can be reduced by over 40 % using voltage injection, by taking advantage of the fact that the MMSPC can parallelize battery-modules when the output voltage is low. This may allow battery degradation to be reduced and the range of an electric vehicle with an MMSPC-system to be increased.

Closed‑loop optimal and automatic tuning of pulse amplitude and width in EMG‑guided controllable transcranial magnetic stimulation

S. M. Mahdi Alavi,Fidel Vila-Rodriguez,Adam Mahdi,Stefan M. Goetz 대한의용생체공학회 2023 Biomedical Engineering Letters (BMEL) Vol.13 No.2

This paper proposes an efficient algorithm for automatic and optimal tuning of pulse amplitude and width for sequentialparameter estimation (SPE) of the neural membrane time constant and input–output (IO) curve parameters in closed-loopelectromyography-guided (EMG-guided) controllable transcranial magnetic stimulation (cTMS). The proposed SPE is performedby administering a train of optimally tuned TMS pulses and updating the estimations until a stopping rule is satisfiedor the maximum number of pulses is reached. The pulse amplitude is computed by the Fisher information maximization. The pulse width is chosen by maximizing a normalized depolarization factor, which is defined to separate the optimizationand tuning of the pulse amplitude and width. The normalized depolarization factor maximization identifies the critical pulsewidth, which is an important parameter in the identifiability analysis, without any prior neurophysiological or anatomicalknowledge of the neural membrane. The effectiveness of the proposed algorithm is evaluated through simulation. The resultsconfirm satisfactory estimation of the membrane time constant and IO curve parameters for the simulation case. By definingthe stopping rule based on the satisfaction of the convergence criterion with tolerance of 0.01 for 5 consecutive times forall parameters, the IO curve parameters are estimated with 52 TMS pulses, with absolute relative estimation errors (AREs)of less than 7%. The membrane time constant is estimated with 0.67% ARE, and the pulse width value tends to the criticalpulse width with 0.16% ARE with 52 TMS pulses. The results confirm that the pulse width and amplitude can be tunedoptimally and automatically to estimate the membrane time constant and IO curve parameters in real-time with closed-loopEMG-guided cTMS.