Context-aware home monitoring system for Parkinson's disease patietns : ambient and werable sensing for freezing of gait detection

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Technische Universiteit Eindhoven. This PhD Thesis has been developed in the framework of, and according to, the rules of the Erasmus Mundus Joint Doctorate on Interactive and Cognitive Environments EMJD ICE [FPA no. 2010-0012]Parkinson’s disease (PD). It is characterized by brief episodes of inability to step, or by extremely short steps that typically occur on gait initiation or on turning while walking. The consequences of FOG are aggravated mobility and higher affinity to falls, which have a direct effect on the quality of life of the individual. There does not exist completely effective pharmacological treatment for the FOG phenomena. However, external stimuli, such as lines on the floor or rhythmic sounds, can focus the attention of a person who experiences a FOG episode and help her initiate gait. The optimal effectiveness in such approach, known as cueing, is achieved through timely activation of a cueing device upon the accurate detection of a FOG episode. Therefore, a robust and accurate FOG detection is the main problem that needs to be solved when developing a suitable assistive technology solution for this specific user group. This thesis proposes the use of activity and spatial context of a person as the means to improve the detection of FOG episodes during monitoring at home. The thesis describes design, algorithm implementation and evaluation of a distributed home system for FOG detection based on multiple cameras and a single inertial gait sensor worn at the waist of the patient. Through detailed observation of collected home data of 17 PD patients, we realized that a novel solution for FOG detection could be achieved by using contextual information of the patient’s position, orientation, basic posture and movement on a semantically annotated two-dimensional (2D) map of the indoor environment. We envisioned the future context-aware system as a network of Microsoft Kinect cameras placed in the patient’s home that interacts with a wearable inertial sensor on the patient (smartphone). Since the hardware platform of the system constitutes from the commercial of-the-shelf hardware, the majority of the system development efforts involved the production of software modules (for position tracking, orientation tracking, activity recognition) that run on top of the middle-ware operating system in the home gateway server. The main component of the system that had to be developed is the Kinect application for tracking the position and height of multiple people, based on the input in the form of 3D point cloud data. Besides position tracking, this software module also provides mapping and semantic annotation of FOG specific zones on the scene in front of the Kinect. One instance of vision tracking application is supposed to run for every Kinect sensor in the system, yielding potentially high number of simultaneous tracks. At any moment, the system has to track one specific person - the patient. To enable tracking of the patient between different non-overlapped cameras in the distributed system, a new re-identification approach based on appearance model learning with one-class Support Vector Machine (SVM) was developed. Evaluation of the re-identification method was conducted on a 16 people dataset in a laboratory environment. Since the patient orientation in the indoor space was recognized as an important part of the context, the system necessitated the ability to estimate the orientation of the person, expressed in the frame of the 2D scene on which the patient is tracked by the camera. We devised method to fuse position tracking information from the vision system and inertial data from the smartphone in order to obtain patient’s 2D pose estimation on the scene map. Additionally, a method for the estimation of the position of the smartphone on the waist of the patient was proposed. Position and orientation estimation accuracy were evaluated on a 12 people dataset. Finally, having available positional, orientation and height information, a new seven-class activity classification was realized using a hierarchical classifier that combines height-based posture classifier with translational and rotational SVM movement classifiers. Each of the SVM movement classifiers and the joint hierarchical classifier were evaluated in the laboratory experiment with 8 healthy persons. The final context-based FOG detection algorithm uses activity information and spatial context information in order to confirm or disprove FOG detected by the current state-of-the-art FOG detection algorithm (which uses only wearable sensor data). A dataset with home data of 3 PD patients was produced using two Kinect cameras and a smartphone in synchronized recording. The new context-based FOG detection algorithm and the wearable-only FOG detection algorithm were both evaluated with the home dataset and their results were compared. The context-based algorithm very positively influences the reduction of false positive detections, which is expressed through achieved higher specificity. In some cases, context-based algorithm also eliminates true positive detections, reducing sensitivity to the lesser extent. The final comparison of the two algorithms on the basis of their sensitivity and specificity, shows the improvement in the overall FOG detection achieved with the new context-aware home system.Esta tesis propone el uso de la actividad y el contexto espacial de una persona como medio para mejorar la detección de episodios de FOG (Freezing of gait) durante el seguimiento en el domicilio. La tesis describe el diseño, implementación de algoritmos y evaluación de un sistema doméstico distribuido para detección de FOG basado en varias cámaras y un único sensor de marcha inercial en la cintura del paciente. Mediante de la observación detallada de los datos caseros recopilados de 17 pacientes con EP, nos dimos cuenta de que se puede lograr una solución novedosa para la detección de FOG mediante el uso de información contextual de la posición del paciente, orientación, postura básica y movimiento anotada semánticamente en un mapa bidimensional (2D) del entorno interior. Imaginamos el futuro sistema de consciencia del contexto como una red de cámaras Microsoft Kinect colocadas en el hogar del paciente, que interactúa con un sensor de inercia portátil en el paciente (teléfono inteligente). Al constituirse la plataforma del sistema a partir de hardware comercial disponible, los esfuerzos de desarrollo consistieron en la producción de módulos de software (para el seguimiento de la posición, orientación seguimiento, reconocimiento de actividad) que se ejecutan en la parte superior del sistema operativo del servidor de puerta de enlace de casa. El componente principal del sistema que tuvo que desarrollarse es la aplicación Kinect para seguimiento de la posición y la altura de varias personas, según la entrada en forma de punto 3D de datos en la nube. Además del seguimiento de posición, este módulo de software también proporciona mapeo y semántica. anotación de zonas específicas de FOG en la escena frente al Kinect. Se supone que una instancia de la aplicación de seguimiento de visión se ejecuta para cada sensor Kinect en el sistema, produciendo un número potencialmente alto de pistas simultáneas. En cualquier momento, el sistema tiene que rastrear a una persona específica - el paciente. Para habilitar el seguimiento del paciente entre diferentes cámaras no superpuestas en el sistema distribuido, se desarrolló un nuevo enfoque de re-identificación basado en el aprendizaje de modelos de apariencia con one-class Suport Vector Machine (SVM). La evaluación del método de re-identificación se realizó con un conjunto de datos de 16 personas en un entorno de laboratorio. Dado que la orientación del paciente en el espacio interior fue reconocida como una parte importante del contexto, el sistema necesitaba la capacidad de estimar la orientación de la persona, expresada en el marco de la escena 2D en la que la cámara sigue al paciente. Diseñamos un método para fusionar la información de seguimiento de posición del sistema de visión y los datos de inercia del smartphone para obtener la estimación de postura 2D del paciente en el mapa de la escena. Además, se propuso un método para la estimación de la posición del Smartphone en la cintura del paciente. La precisión de la estimación de la posición y la orientación se evaluó en un conjunto de datos de 12 personas. Finalmente, al tener disponible información de posición, orientación y altura, se realizó una nueva clasificación de actividad de seven-class utilizando un clasificador jerárquico que combina un clasificador de postura basado en la altura con clasificadores de movimiento SVM traslacional y rotacional. Cada uno de los clasificadores de movimiento SVM y el clasificador jerárquico conjunto se evaluaron en el experimento de laboratorio con 8 personas sanas. El último algoritmo de detección de FOG basado en el contexto utiliza información de actividad e información de texto espacial para confirmar o refutar el FOG detectado por el algoritmo de detección de FOG actual. El algoritmo basado en el contexto influye muy positivamente en la reducción de las detecciones de falsos positivos, que se expresa a través de una mayor especificidadPostprint (published version

Context-aware home monitoring system for Parkinson's disease patietns : ambient and werable sensing for freezing of gait detection

Parkinson’s disease (PD). It is characterized by brief episodes of inability to step, or by extremely short steps that typically occur on gait initiation or on turning while walking. The consequences of FOG are aggravated mobility and higher affinity to falls, which have a direct effect on the quality of life of the individual. There does not exist completely effective pharmacological treatment for the FOG phenomena. However, external stimuli, such as lines on the floor or rhythmic sounds, can focus the attention of a person who experiences a FOG episode and help her initiate gait. The optimal effectiveness in such approach, known as cueing, is achieved through timely activation of a cueing device upon the accurate detection of a FOG episode. Therefore, a robust and accurate FOG detection is the main problem that needs to be solved when developing a suitable assistive technology solution for this specific user group. This thesis proposes the use of activity and spatial context of a person as the means to improve the detection of FOG episodes during monitoring at home. The thesis describes design, algorithm implementation and evaluation of a distributed home system for FOG detection based on multiple cameras and a single inertial gait sensor worn at the waist of the patient. Through detailed observation of collected home data of 17 PD patients, we realized that a novel solution for FOG detection could be achieved by using contextual information of the patient’s position, orientation, basic posture and movement on a semantically annotated two-dimensional (2D) map of the indoor environment. We envisioned the future context-aware system as a network of Microsoft Kinect cameras placed in the patient’s home that interacts with a wearable inertial sensor on the patient (smartphone). Since the hardware platform of the system constitutes from the commercial of-the-shelf hardware, the majority of the system development efforts involved the production of software modules (for position tracking, orientation tracking, activity recognition) that run on top of the middle-ware operating system in the home gateway server. The main component of the system that had to be developed is the Kinect application for tracking the position and height of multiple people, based on the input in the form of 3D point cloud data. Besides position tracking, this software module also provides mapping and semantic annotation of FOG specific zones on the scene in front of the Kinect. One instance of vision tracking application is supposed to run for every Kinect sensor in the system, yielding potentially high number of simultaneous tracks. At any moment, the system has to track one specific person - the patient. To enable tracking of the patient between different non-overlapped cameras in the distributed system, a new re-identification approach based on appearance model learning with one-class Support Vector Machine (SVM) was developed. Evaluation of the re-identification method was conducted on a 16 people dataset in a laboratory environment. Since the patient orientation in the indoor space was recognized as an important part of the context, the system necessitated the ability to estimate the orientation of the person, expressed in the frame of the 2D scene on which the patient is tracked by the camera. We devised method to fuse position tracking information from the vision system and inertial data from the smartphone in order to obtain patient’s 2D pose estimation on the scene map. Additionally, a method for the estimation of the position of the smartphone on the waist of the patient was proposed. Position and orientation estimation accuracy were evaluated on a 12 people dataset. Finally, having available positional, orientation and height information, a new seven-class activity classification was realized using a hierarchical classifier that combines height-based posture classifier with translational and rotational SVM movement classifiers. Each of the SVM movement classifiers and the joint hierarchical classifier were evaluated in the laboratory experiment with 8 healthy persons. The final context-based FOG detection algorithm uses activity information and spatial context information in order to confirm or disprove FOG detected by the current state-of-the-art FOG detection algorithm (which uses only wearable sensor data). A dataset with home data of 3 PD patients was produced using two Kinect cameras and a smartphone in synchronized recording. The new context-based FOG detection algorithm and the wearable-only FOG detection algorithm were both evaluated with the home dataset and their results were compared. The context-based algorithm very positively influences the reduction of false positive detections, which is expressed through achieved higher specificity. In some cases, context-based algorithm also eliminates true positive detections, reducing sensitivity to the lesser extent. The final comparison of the two algorithms on the basis of their sensitivity and specificity, shows the improvement in the overall FOG detection achieved with the new context-aware home system.Esta tesis propone el uso de la actividad y el contexto espacial de una persona como medio para mejorar la detección de episodios de FOG (Freezing of gait) durante el seguimiento en el domicilio. La tesis describe el diseño, implementación de algoritmos y evaluación de un sistema doméstico distribuido para detección de FOG basado en varias cámaras y un único sensor de marcha inercial en la cintura del paciente. Mediante de la observación detallada de los datos caseros recopilados de 17 pacientes con EP, nos dimos cuenta de que se puede lograr una solución novedosa para la detección de FOG mediante el uso de información contextual de la posición del paciente, orientación, postura básica y movimiento anotada semánticamente en un mapa bidimensional (2D) del entorno interior. Imaginamos el futuro sistema de consciencia del contexto como una red de cámaras Microsoft Kinect colocadas en el hogar del paciente, que interactúa con un sensor de inercia portátil en el paciente (teléfono inteligente). Al constituirse la plataforma del sistema a partir de hardware comercial disponible, los esfuerzos de desarrollo consistieron en la producción de módulos de software (para el seguimiento de la posición, orientación seguimiento, reconocimiento de actividad) que se ejecutan en la parte superior del sistema operativo del servidor de puerta de enlace de casa. El componente principal del sistema que tuvo que desarrollarse es la aplicación Kinect para seguimiento de la posición y la altura de varias personas, según la entrada en forma de punto 3D de datos en la nube. Además del seguimiento de posición, este módulo de software también proporciona mapeo y semántica. anotación de zonas específicas de FOG en la escena frente al Kinect. Se supone que una instancia de la aplicación de seguimiento de visión se ejecuta para cada sensor Kinect en el sistema, produciendo un número potencialmente alto de pistas simultáneas. En cualquier momento, el sistema tiene que rastrear a una persona específica - el paciente. Para habilitar el seguimiento del paciente entre diferentes cámaras no superpuestas en el sistema distribuido, se desarrolló un nuevo enfoque de re-identificación basado en el aprendizaje de modelos de apariencia con one-class Suport Vector Machine (SVM). La evaluación del método de re-identificación se realizó con un conjunto de datos de 16 personas en un entorno de laboratorio. Dado que la orientación del paciente en el espacio interior fue reconocida como una parte importante del contexto, el sistema necesitaba la capacidad de estimar la orientación de la persona, expresada en el marco de la escena 2D en la que la cámara sigue al paciente. Diseñamos un método para fusionar la información de seguimiento de posición del sistema de visión y los datos de inercia del smartphone para obtener la estimación de postura 2D del paciente en el mapa de la escena. Además, se propuso un método para la estimación de la posición del Smartphone en la cintura del paciente. La precisión de la estimación de la posición y la orientación se evaluó en un conjunto de datos de 12 personas. Finalmente, al tener disponible información de posición, orientación y altura, se realizó una nueva clasificación de actividad de seven-class utilizando un clasificador jerárquico que combina un clasificador de postura basado en la altura con clasificadores de movimiento SVM traslacional y rotacional. Cada uno de los clasificadores de movimiento SVM y el clasificador jerárquico conjunto se evaluaron en el experimento de laboratorio con 8 personas sanas. El último algoritmo de detección de FOG basado en el contexto utiliza información de actividad e información de texto espacial para confirmar o refutar el FOG detectado por el algoritmo de detección de FOG actual. El algoritmo basado en el contexto influye muy positivamente en la reducción de las detecciones de falsos positivos, que se expresa a través de una mayor especificida

Postrna proizvodnja kupusa u Srbiji

Cabbage is an important vegetable crop that is grown at 20,891 ha in Serbia. Growing cabbage as a double crop intensifies land use and increases the profitability of crop production. Double cropping of cabbage is a well-established practice in Serbia. Domestic cultivars and populations of cabbage predominate in the commercial production and this choice of assortment dictates the subsequent use of the harvested cabbage crop. The two main types of use are fresh consumption and pickling. Under Serbian growing conditions, the optimum time for late cabbage transplanting is the first half of July, a period characterized by high temperatures and insufficient and unevenly distributed rainfall. Growing cabbages during this period without the help of irrigation is a fairly risky proposition. Late cabbage cultivars and hybrids must be harvested before temperatures drops below -5°C. Cabbage can survive temperatures of -4°C to -5°C for only a limited period of time and prolonged exposure to such conditions will result in the plant being winterkilled and the head losing its market value.Kupus je značajna povrtarska kultura koja se u Srbiji proizvodi na 20.891 ha. Gajenje kupusa kao druge kulture (tj. postrno) omogućuje intenzivno korišćenje zemljišta i rentabilniju prizvodnju. Kasna ili postrna proizvodnja kupusa u Srbiji ima svoju tradiciju. Relativno često se gaje domaće sorte i populacije kupusa koje definišu i način potrošnje, što je pre svega sveža upotreba, ali i sve prisutnije kišeljenje kupusa. Optimalni rok za rasađivanje kasnog kupusa u agroklimatskim uslovima Srbije je prva polovina jula. Ovaj period karakterišu visoke temperature i nedovoljna količina padavina neravnomernog rasporeda, tako da je proizvodnja kupusa bez navodnjavanja nesigurna. Kod kasnih sorti i hibrida kupusa berba se mora organizovati pre nego što temperatura padne ispod -5°C. Na -4°C i -5°C kupus može da bude samo privremeno, jer posle dužeg vremena dolazi do izmrzavanja i gubljenja tržišne vrednosti glavica kupusa

Utjecaj supstituenata na NMR značajke temeljnog bicikličkog prstenastog sustava fluorokinolonskih antibiotika, odnos između NMR kemijskih pomaka, molekulskih opisivača i parametara sličnosti s lijekovima

In the present study, the NMR spectroscopic features of trovafloxacin (TVA) mesylate, pefloxacin (PFX) mesylate dihydrate and ciprofloxacin (CIP) hydrochloride monohydrate were studied in DMSO-d6 solution with the aim of investigating the effects of substituents and the type of salt on the NMR parameters of basic bicyclic fluoroquinolone and fluoronaphthyridone ring systems. For this purpose, the 1H- and 13C- one- and two-dimensional homo- and heteronuclear NMR methods were used. The analysis of 1H- and 13C-NMR spectra confirmed the structures of investigated fluoroquinolone salts. Relationship between 1H- and 13C-NMR chemical shifts of fluoronaphthyridone and fluoroquinolone ring systems and calculated molecular descriptors (MDs) and drug-likeness scores (DLSs), computed for monoprotonic cations of investigated fluoroquinolone salts (TVAH+, PFXH+ and CIPH+) were also explored. The topological polar surface area (TPSA), the parameter of lipophylicity (miLogP), the relative molecular mass (Mr) and the volume (V) of computed molecular descriptors (MDs), as well as the G protein-coupled receptor ligand-likeness (GPCR ligand-ls), the ion channel ligand-likeness (ICL-ls), the kinase inhibitor-likeness (KI-ls) and the nuclear receptor ligand-likeness (NRL-ls) were used in this study. The 1H-NMR chemical shifts of protons in COOH, H5 and NHn+, as well as 13C NMR chemical shifts of C4, C5 and C11 shown to be good parameters in exploration of property-property and property-drug-likeness relationships for investigated fluoroquinolone salts. Thus, collinear relationships between 1H-NMR chemical shifts of protons in COOH, H5 and NHn+ with TPSA and miLogP, as well as with GPCR ligand-ls), KI-ls and NRL-ls were revealed (, ppm H in COOH vs. TPSA, R = 0.9421; , ppm H in COOH vs. NRL-ls, R = 0.9216; , ppm H5 vs. miLogP, R = 0.9962; , ppm H5 vs. KI-ls, R = 0.9969; , ppm NHn+ vs. TPSA, R = 0.9875 and , ppm NHn+ vs. NRL-ls, R = 0.9948). The collinearities between 13C-NMR chemical shifts of C4, C5 and C11 with KI-ls and NRL-ls, as well as with TPSA, miLogP, Mr and V were also revealed (, ppm C4 vs. TPSA, R = 0.9964; , ppm C4 vs. miLogP, R = 0.9487; , ppm C4 vs. Mr, R = 0.9629; , ppm C4 vs. KI-ls, R = 0.9461; , ppm C4 vs. NRL-ls, R = 0.9996; , ppm C5 vs. miLogP, R = 0.9994; , ppm C5 vs. KI-ls, R = 0.9990; , ppm C5 vs. NRL-ls, R = 0.9510; , ppm C11 vs. TPSA., R = 0.9958; , ppm C11 vs. NRL-ls, R = 0.9994 and , ppm C11 vs. KI-ls, R = 0.9481).U radu je opisano ispitivanje NMR spektroskopskih značajki trovafloksacin (TVA) mesilata, pefloksacin (PFX) mesilata i ciprofloksacin (CIP) hidroklorida u DMSO-d6 otopini s ciljem da se istraži utjecaj supstituenata i tip soli na NMR parametre bicikličkog fluorokinolonskog i fluoronaftiridonskog prstenastog sustava. Analizom jedno- i dvo-dimenzijskih, homo- i hetero-nuklearnih 1H- i 13C-NMR spektara potvrđena je struktura ispitivanih fluorokinolonskih soli. 1H- i 13C-NMR kemijski pomaci (, ppm) temeljnih prstenastih sustava korelirani su s izračunatim molekulskim opisivačima (relativnom molekulskom masom, Mr, topologijskom polarnom površinom, TPSA, lipofilnošću, miLogP i s volumenom, V) te s parametrima sličnosti s lijekovima poznate biološke aktivnosti, tj. s ligandom G protein-spregnutog receptora (GPCR ligand), ligandom ionskih kanala (ICL), inhibitorom kinaze (KI) i ligandom nuklearnog receptora (NRL) koji su izračunati za monoprotonske katione ispitivanih fluorokinolonskih soli (TVAH+, PFXH+ and CIPH+). 13C-NMR kemijski pomaci (/ppm) C4, C5 i C11 atoma i 1H-NMR kemijski pomaci (/ppm) protona u COOH, H5 i NHn+ ispitivanih fluorokinolonskih soli pokazali su se kao dobri parametri za istraživanje odnosa svojstvo-svojstvo i svojstvo-sličnost s lijekovima poznate biološke aktivnosti. Tako je otkriven kolinearan odnos između 13C-NMR kemijskih pomaka (/ppm) C4, C5 i C11 atoma i izračunatih parametara za sličnost s kinaza inhibitorom (KI-ls) i ligandom nuklearnog receptora (NRL-ls) pored kolinearnosti s TPSA, miLogP, Mr i V (C4 /ppm s TPSA, R = 0,9964; C4 /ppm s miLogP, R = 0,9487; C4 /ppm s Mr, R = 0,9629; C4 /ppm s V, R = 0,8547; C4 /ppm s KI-ls, R = 0,9461 i C4 /ppm s NRL-ls, R = 0,9996; C5 s miLogP, R = 0,9994; C5 s KI-ls, R = 0,9990 i C5 s NRL-ls, R = 0,9510; C11 s TPSA, R = 0,9958; C11 /ppm s KI-ls, R = 0,9481 i C11 /ppm s NRL-ls, R = 0,9994). 1H-NMR kemijski pomaci (/ppm) protona COOH, H5 i NHn+ pokazali su kolinearanost odnosa s TPSA i miLogP, te s izračunatim parametrima za sličnost s kinaza inhibitorom (KI-ls), ligandom nuklearnog receptora (NRL-ls) i GPCR ligandom (GPCRl-ls) (/ppm H u COOH s TPSA, R = 0,9421; /ppm H u COOH s NRL-ls, R = 0,9216; H5 /ppm s miLogP, R = 0,9962; /ppm H5 s KI-ls, R = 0,9969; /ppm NHn+ s TPSA, R = 0,9875; /ppm NHn+ s NRL-ls, R = 0,9948; /ppm NHn+ s GPCR ligandom, R = 0,9873). Rezultati istraživanja su pokazali razliku u eksperimentalnim i izračunatim parametrima za trovafloksacin mesilat u usporedbi s pefloksacin mesilatom i ciprofloksacin hidrokloridom, te je nađena značajna kolinearnost među ispitivanim parametrima ovih fluorokinolonskih antibiotika

Influence of tomato genotype to phenolic compounds content and antioxidant activity as reaction to early blight

Early blight is one of the most common and destructive tomato disease and it is caused by the fungus Alternaria solani. The aim of this paper was to screen the reaction of ten tomato genotypes (collection of the Institute of Field and Vegetable Crops) against natural infection of early blight. Tested genotypes showed significant differences in the disease occurrence on leaves but not on fruits. However, at the biochemical level, total phenolics (TP), tannins (TT), flavonoids (TF) and antioxidant activity in tomato fruits was significantly affected by genotype, disease occurrence and interaction of these two factors. According to obtained results, content of these secondary metabolites could be used as a one of the parameters in the evaluation of tomato resistance to EB

The Homogeneity Range in the System UP(O)

A large number of samples of uranium monorphosphide were prepared by direct reaction between uranium filings and red phosphor us, followed by homogenization in a high temperature furnace (Degussa) at 1200-1300 °c and a pres,sure of 10-4 Torr (1 Torr = 101.325/760 kPa). Samples were analyzed for uranium, phosphorus and nitrogen, assuming that the difference is oxygen. The oxygen content wa.s found to vary from sample to sample, ranging from 0.54 (min.) up to 7.10 wt. O/o (max.). X-ray analysis did not indicate the presence of U02• The amount of oxygen or nitrogen was not controled in advance, but final results ensured the working hypothesis, since the analytical data were in acordance with the X-ray powder diagrams

Acquisition of English nominal suffix -er by advanced EFL learners: a view from usage-based perspective

The present study investigated advanced Croatian EFL learners’ knowledge of five mean-ings of the English nominal (deverbal) suffix -er. It probed their ability to comprehend and produce corpus-rare and presumably unentrenched -er nouns in their prototypical agent and instrument meanings and their non-prototypical patient, locative, and causative meanings. It was hypothesized that participants would deal effortlessly with agent and instrument meanings of the low-frequency nouns since the corpus-attested high type frequency of -er agents and instruments, among others, suggests the existence of productive correspond-ing schemas. We hypothesized that participants would struggle with patient, locative and causative meanings of the low-frequency nouns since the corpus-attested low type frequency of the three functions arguably does not support their association with -er. A recognition and a production test were administered to two separate groups of English majors at a Croatian public university (n = 131). Results confirm general usage-based predictions about better performance with low-frequency agent and instrument -er nouns. However, a detailed examination reveals unexpected results, which confirm that frequency, however important, is not the only factor to include in a future model of EFL learners’ derivational proficiency