Gli autori riconoscono Evan Beisheim, Nicole Capela, Andrew Herbert-Copley per l&#39;assistenza tecnica e la raccolta dei dati. Il finanziamento dei progetti è stato ricevuto dalle scienze naturali e ingegneria Research Council del Canada (NSERC) e BlackBerry Ltd., inclusi smartphone utilizzati nello studio.

Questo protocollo è stato approvato dal Consiglio di Ricerca Etica Ottawa Health Science Network. 1. Preparazione <ol><li> Fornire ai partecipanti un quadro della ricerca, rispondere alle domande, e ottenere il consenso informato. Caratteristiche dei partecipanti record (ad esempio, età, sesso, altezza, peso, circonferenza vita, altezza gamba dal spinale anteriore superiore iliaca al malleolo mediale), il codice di identificazione, e la data su una scheda tecnica. Verificare che il secondo smartphone che viene utilizzata per catturare video è impostato su almeno 30 fotogrammi al secondo tasso di acquisizione. </li><li> Trovare e collegare una fondina per telefono anteriore destra cintura o mutanda vita del partecipante. Avviare l&#39;applicazione per smartphone che verrà utilizzato per raccogliere i dati del sensore (ad esempio, di registrazione dei dati o di applicazione WMMS) sullo smartphone di misura di mobilità e assicurare che l&#39;applicazione è in esecuzione in modo appropriato. Posizionare lo smartphone nella custodia, con la parte posteriore del dispositivo (ca posterioreMera) rivolto verso l&#39;esterno. </li><li> Avviare la registrazione video digitale su un secondo smartphone. Per l&#39;anonimato, registrare il video confronto senza mostrare il volto della persona, ma assicurarsi di registrare tutte le transizioni di attività. Il telefono può essere tenuto in mano. </li></ol> 2. Circuito Attività <ol><li> Seguire il partecipante e il video le loro azioni, il secondo smartphone, mentre compiono le seguenti azioni, pronunciate dal ricercatore: <ol><li> Da una posizione eretta, agitare lo smartphone per indicare l&#39;inizio del processo. </li><li> Continuare in piedi per almeno 10 secondi. Questa fase in piedi può essere utilizzato per la calibrazione orientamento telefono 14. </li><li> A piedi da una sedia e sedersi. </li><li> Alzarsi e camminare 60 metri di un ascensore. </li><li> Stand e aspettare l&#39;ascensore e poi a piedi in ascensore. </li><li> Prendete l&#39;ascensore fino al secondo piano. </li><li> Girare e camminare in ambiente domestico. </li><li> Entrate in bagno e siMulate lavarsi i denti. </li><li> Simulare pettinatura dei capelli. </li><li> Simulare lavarsi le mani. </li><li> Asciugare le mani con un asciugamano. </li><li> A piedi in cucina. </li><li> Prendete i piatti da un rack e metterli sul banco. </li><li> Riempire una pentola con l&#39;acqua del lavandino della cucina. </li><li> Posizionare il bollitore sul fornello elemento. </li><li> Mettere il pane in un tostapane. </li><li> A piedi dalla sala da pranzo. </li><li> Sedersi a un tavolo da pranzo. </li><li> Simulare mangiare un pasto a tavola. </li><li> Alzarsi e camminare di nuovo al lavello della cucina. </li><li> Risciacquare i piatti e metterli in un rack. </li><li> A piedi dalla cucina di nuovo verso l&#39;ascensore. </li><li> Stand e aspettare l&#39;ascensore e poi a piedi in ascensore. </li><li> Prendete l&#39;ascensore fino al primo piano. </li><li> A piedi a 50 metri di una tromba delle scale. </li><li> Aprire la porta ed entrate nella tromba delle scale. </li><li> Salire le scale (13 gradini, circa atterraggio, 13 scalini). </li><li> Aprire la porta delle scale nel corridoio. </li><li> Girare a destra e proseguire a piedi lungo il corridoio per 15 metri. </li><li> Girarsi e camminare 15 metri di nuovo alla tromba delle scale. </li><li> Aprire la porta ed entrate nella tromba delle scale. </li><li> Proseguire a piedi lungo le scale (13 gradini, circa atterraggio, 13 scalini). </li><li> Uscire dalla tromba delle scale e entrare in una stanza. </li><li> Sdraiatevi su un letto. </li><li> Alzati e cammina 10 metri ad una rampa. </li><li> Salite la rampa, girare intorno, poi giù per la rampa (20 metri). </li><li> Proseguire a piedi nel corridoio ed aprite la porta verso l&#39;esterno. </li><li> Camminare per 100 metri sul sentiero lastricato. </li><li> Girare intorno e tornare indietro per la stanza. </li><li> Camminare nella stanza e stare al punto di partenza. </li><li> Continuare in piedi, e poi agitare lo smartphone per indicare la fine della prova. </li></ol></li></ol> 3. Completamento Trial <ol><li> Fermare lo smartphone di registrazione video e chiedere al partecipante di rimuovere e restituire lo smartphone e fondina. Arrestare la registrazione dei dati o l&#39;applicazione WMMS sulla SMARTphone. Copiare i file di dati acquisiti movimento e il file video da entrambi i telefoni a un computer per la post-elaborazione. </li></ol> 4. post-elaborazione <ol><li> Sincronizzazione temporale tra il video ei dati grezzi sensore determinando il momento in cui l&#39;azione shake iniziato. Questo movimento agitando corrisponde ad un telaio segnale dell&#39;accelerometro e il video distinti. Verificare la presenza di errore di sincronizzazione sottraendo il tempo scossa fine dal momento scossa di inizio, per le origini dati di sensori e video. Differenze di tempo dovrebbero essere simili tra i due insiemi di dati. </li><li> Determinare i tempi effettivi di cambiamento di stato dal video gold-standard registrando la differenza di tempo dal momento in scossa inizio per il fotogramma video nel passaggio tra le attività. Utilizzare software di editing video per ottenere i tempi entro 0,033 sec (ad esempio, 30 fotogrammi al secondo tasso di video). Utilizzare il software WMMS per generare cambiamenti-of-state analoghe, i dati del sensore. </li><li> Generare due insiemi di dati, unocon veri attività e la seconda con attività previste, etichettando l&#39;attività per ogni fotogramma video (in base al cambiamento di temporizzazione di stato) e poi calcolando l&#39;attività prevista in ogni fotogramma video dall&#39;uscita WMMS. Per la valutazione delle prestazioni WMMS, calcolare veri positivi, falsi negativi, veri negativi, falsi positivi tra l&#39;attività gold-standard e WMMS predetto attività. Utilizzare questi parametri per calcolare misure esiti sensibilità, specificità, e F-score. Nota: L&#39;impostazione di tolleranza di 3 finestre di dati su entrambi i lati della finestra analizzato può essere utilizzato per determinare i risultati di cambiamento di stato, e 2 finestre di dati per i risultati di classificazione. Ad esempio, dal 1 finestre secondi dati sono stati utilizzati per la WMMS in questo studio, 3 sec prima e dopo la finestra corrente sono stati esaminati in modo che i cambiamenti consecutivi all&#39;interno della stessa tolleranza vengono ignorati. Il corrispettivo è stato che i cambiamenti di stato che avvengono in meno di 3 secondi può essere ignorato per Huma lordoanalisi del movimento n in quanto questi Stati sarebbe considerato transitorio. </li></ol>

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L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Review+of+Accelerometry-Based+Wearable+Motion+Detectors+for+Physical+Activity+Monitoring.">A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring.</a> Sensors. 10 (8), 7772-7788 (2010).</li><li>He, Y., Li, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physical+Activity+Recognition+Utilizing+the+Built-In+Kinematic+Sensors+of+a+Smartphone.">Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone.</a> International Journal of Distributed Sensor Networks. 2013, (2013).</li><li>Vo, Q. V., Hoang, M. T., Choi, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Personalization+in+Mobile+Activity+Recognition+System+using+K-medoids+Clustering+Algorithm.">Personalization in Mobile Activity Recognition System using K-medoids Clustering Algorithm.</a> International Journal of Distributed Sensor Networks. 2013, (2013).</li><li>Dernbach, S., Das, B., Krishnan, N. C., Thomas, B. L., Cook, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simple+and+Complex+Activity+Recognition+through+Smart+Phones.">Simple and Complex Activity Recognition through Smart Phones.</a> , 214-221 (2012).</li><li>Hache, G., Lemaire, E. 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The authors declare that they have no competing financial interests.

Riconoscimento L&#39;attività umana, con un sistema di monitoraggio della mobilità indossabile ha ricevuto più attenzione negli ultimi anni grazie ai progressi tecnici nel campo dell&#39;informatica e smartphone indossabili e le esigenze sistematici per misure quantitative di esito che aiutano con processo decisionale clinico e valutazione intervento sanitario. La metodologia descritta nel presente documento è stato efficace per valutare lo sviluppo WMMS poiché si è constatato che non sarebbe stato presente se una...

Rilevamento onnipresente è diventata un&#39;area di ricerca coinvolgente a causa di sempre più potenti, piccolo, di calcolo a basso costo e apparecchiature di rilevamento 1. Mobilità monitoraggio tramite sensori indossabili ha generato un grande interesse da microelettronica a livello dei consumatori siano in grado di rilevare caratteristiche di movimento con elevata precisione 1. Riconoscimento L&#39;attività umana (HAR) utilizzando sensori indossabili è una recente settore della ricerca, con studi preliminari effettuati negli anni 1980 e 1990 2-4. Moderni smartphone contengono i sensori necessari e la capacità di calcolo in tempo reale per il riconoscimento di attività di mobilità. Analisi in tempo reale sul dispositivo consente classificazione delle attività e caricamento dei dati, senza l&#39;intervento dell&#39;utente o investigatore. Uno smartphone con il software di analisi della mobilità potrebbe fornire fitness tracking, il monitoraggio sanitario, cadere rilevamento di casa e l&#39;automazione di lavoro, e di auto-gestione exercisprogrammi di e 5. Gli smartphone possono essere considerati piattaforme di misura inerziale per la rilevazione di attività mobili e modelli di mobili negli esseri umani, con caratteristiche di segnale matematici generati calcolati con uscite del sensore a bordo 6. Metodi di generazione di funzionalità comuni includono euristica, nel dominio del tempo, nel dominio della frequenza, e wavelet approcci di analisi basati su 7. Sistemi smartphone HAR moderni hanno mostrato elevate precisioni di previsione quando rileva attività specificate 1,5,6,7. Questi studi variano in metodologia di valutazione, così come la precisione da maggior parte degli studi hanno un proprio insieme di addestramento, l&#39;installazione ambientale, e il protocollo di raccolta dei dati. La sensibilità, la specificità, la precisione, richiamo, precisione, e F-Score sono comunemente usati per descrivere la qualità previsione. Tuttavia, a poco a non sono disponibili informazioni sui metodi per il riconoscimento &quot;attività simultanee&quot; e valutazione della capacità di rilevare i cambiamenti di attività in tempo reale1, per i sistemi HAR che tentano di classificare diverse attività. Metodi di valutazione per HAR precisione del sistema variano notevolmente tra gli studi. Indipendentemente dal algoritmo di classificazione o funzioni applicate, le descrizioni dei metodi di valutazione standard di oro sono vaghi per la maggior parte della ricerca HAR. Il riconoscimento di attività in un ambiente di vita quotidiana non è stato ampiamente studiato. La maggior parte dei sistemi di riconoscimento di attività basati smartphone-sono valutate in modo controllato, portando ad un protocollo di valutazione che può essere vantaggioso per l&#39;algoritmo piuttosto che realistico un ambiente reale. All&#39;interno del loro schema di valutazione, i partecipanti spesso eseguono solo le azioni previste per la previsione, piuttosto che l&#39;applicazione di una vasta gamma di attività realistici per il partecipante di eseguire consecutivamente, imitando eventi della vita reale. Alcuni HAR smartphone studia 8,9 gruppo attività simili insieme, come scale e passeggiate, Ma escludere altre attività dal set di dati. Accuratezza previsione è quindi determinato da quanto bene l&#39;algoritmo ha individuato le attività target. Dernbach et al. 9 hanno avuto partecipanti scrivono l&#39;attività che stavano per eseguire, prima di trasferirsi, di interrompere le transizioni continue di cambiamento di stato. Le valutazioni del sistema HAR dovrebbero valutare l&#39;algoritmo mentre il partecipante compie azioni naturali in un ambiente vita quotidiana. Ciò consentirebbe una valutazione in vivo che riproduce l&#39;uso quotidiano dell&#39;applicazione. Un circuito realistico include molti cambiamenti di stato e un insieme di azioni non prevedibili dal sistema. Un investigatore può quindi valutare la risposta dell&#39;algoritmo di questi movimenti supplementari, valutando in tal modo la robustezza dell&#39;algoritmo di movimenti anomali. Questo articolo presenta un protocollo di valutazione Wearable Mobility System Monitoring (WMMS) che utilizza un percorso controllato che riflette ambienti di vita quotidiana della vita reale. WMMSvalutazione può quindi essere effettuata in condizioni controllate, ma realistiche. In questo protocollo, si usa un WMMS terza generazione che è stato sviluppato presso l&#39;Università di Ottawa e Ottawa Hospital Research Institute 11-15. Il WMMS è stato progettato per gli smartphone con un accelerometro a tre assi e giroscopio. Conti L&#39;algoritmo mobilità variabilità utente, fornisce una riduzione del numero di falsi positivi per l&#39;identificazione cambiamenti di stato, e aumenta la sensibilità nell&#39;attività categorizzazione. Minimizzare falsi positivi è importante in quanto la WMMS innesca breve registrazione video clip quando vengono rilevate modifiche di attività di stato, per la valutazione attività sensibile al contesto che migliora ulteriormente la classificazione WMMS. Registrazione video inutile crea inefficienze di immagazzinamento e l&#39;uso della batteria. L&#39;algoritmo WMMS è strutturata come un modello a basso computazionale apprendimento e valutata utilizzando diversi livelli di previsione, in cui un aumento del livello previsione indica un aumento nella quantitàazioni di riconoscibili.

<table border="0" cellpadding="0" cellspacing="0" width="1314">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:516px;">Smartphone or wearable measurement device</td>
			<td style="width:627px;">Blackberry</td>
			<td style="width:108px;">Z10</td>
			<td style="width:64px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Smartphone for video recording</td>
			<td>Blackberry</td>
			<td>Z10 or 9800</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Phone holster</td>
			<td>Any</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Data logger application for the smartphone</td>
			<td>BlackBerry World - TOHRC Data Logger for BlackBerry 10</td>
			<td></td>
			<td><a href="http://appworld.blackberry.com/webstore/content/32013891/?countrycode=CA">http://appworld.blackberry.com/webstore/content/32013891/?countrycode=CA</a></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Wearable mobility measurement</td>
			<td>Custom Blackberry 10 and Matlab software for mobility monitoring</td>
			<td></td>
			<td><a href="http://www.irrd.ca/cag/smartphone/">http://www.irrd.ca/cag/smartphone/</a></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Video editing or analysis software</td>
			<td>Motion Analysis Tools</td>
			<td></td>
			<td><a href="http://www.irrd.ca/cag/mat/">http://www.irrd.ca/cag/mat/</a></td>
		</tr>
	</tbody>
</table>

evaluation of a smartphone-based human activity recognition system in a daily living environment

An evaluation method that includes continuous activities in a daily-living environment was developed for Wearable Mobility Monitoring Systems (WMMS) that attempt to recognize user activities. Participants performed a pre-determined set of daily living actions within a continuous test circuit that included mobility activities (walking, standing, sitting, lying, ascending/descending stairs), daily living tasks (combing hair, brushing teeth, preparing food, eating, washing dishes), and subtle environment changes (opening doors, using an elevator, walking on inclines, traversing staircase landings, walking outdoors). 
To evaluate WMMS performance on this circuit, fifteen able-bodied participants completed the tasks while wearing a smartphone at their right front pelvis. The WMMS application used smartphone accelerometer and gyroscope signals to classify activity states. A gold standard comparison data set was created by video-recording each trial and manually logging activity onset times. Gold standard and WMMS data were analyzed offline. Three classification sets were calculated for each circuit: (i) mobility or immobility, ii) sit, stand, lie, or walking, and (iii) sit, stand, lie, walking, climbing stairs, or small standing movement. Sensitivities, specificities, and F-Scores for activity categorization and changes-of-state were calculated.
The mobile versus immobile classification set had a sensitivity of 86.30% &#177; 7.2% and specificity of 98.96% &#177; 0.6%, while the second prediction set had a sensitivity of 88.35% &#177; 7.80% and specificity of 98.51% &#177; 0.62%. For the third classification set, sensitivity was 84.92% &#177; 6.38% and specificity was 98.17 &#177; 0.62. F1 scores for the first, second and third classification sets were 86.17 &#177; 6.3, 80.19 &#177; 6.36, and 78.42 &#177; 5.96, respectively. This demonstrates that WMMS performance depends on the evaluation protocol in addition to the algorithms. The demonstrated protocol can be used and tailored for evaluating human activity recognition systems in rehabilitation medicine where mobility monitoring may be beneficial in clinical decision-making.

Il protocollo dello studio è stato condotto con un campione di convenienza di quindici partecipanti normodotati il ​​cui peso medio era 68,9 (± 11,1) kg, altezza era 173,9 (± 11.4) cm, e l&#39;età era di 26 (± 9) anni, reclutati da L&#39;ospedale di Ottawa e Università di Ottawa e personale degli studenti. Uno smartphone catturato dati del sensore a una velocità di 40-50 Hz variabile. Variazioni dei tassi di campionamento sono tipiche per il campionamento del sensore smartphone. Un secondo smartphone è stato...

Watch this Scientific Journal Video about Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment at JoVE.com

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

A standardized evaluation method was developed for Wearable Mobility Monitoring Systems (WMMS) that includes continuous activities in a realistic daily living environment. Testing with a series of daily living activities can decrease activity recognition sensitivity; therefore, realistic testing circuits are encouraged for valid evaluation of WMMS performance.

Valutazione di un sistema di riconoscimento attività umana basata-Smartphone in un ambiente di vita quotidiana

An evaluation method that includes continuous activities in a daily-living environment was developed for Wearable Mobility Monitoring Systems (WMMS) that ...

evaluation-smartphone-based-human-activity-recognition-system-daily

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8.8K Views.  University of Ottawa. A standardized evaluation method was developed for Wearable Mobility Monitoring Systems (WMMS) that includes continuous activities in a realistic daily living environment. Testing with a series of daily living activities can decrease activity recognition sensitivity; therefore, realistic testing circuits are encouraged for valid evaluation of WMMS performance.

Video: Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment

In recent years, two-photon imaging has become an invaluable tool in neuroscience, as it allows for chronic measurement of the activity of genetically identified cells during behavior1-6. Here we describe methods to perform two-photon imaging in mouse cortex while the animal navigates a virtual reality environment. We focus on the aspects of the experimental procedures that are key to imaging in a behaving animal in a brightly lit virtual environment. The key problems that arise in this experimental setup that we here address are: minimizing brain motion related artifacts, minimizing light leak from the virtual reality projection system, and minimizing laser induced tissue damage. We also provide sample software to control the virtual reality environment and to do pupil tracking. With these procedures and resources it should be possible to convert a conventional two-photon microscope for use in behaving mice.

Here we describe the experimental procedures involved in two-photon imaging of mouse cortex during behavior in a virtual reality environment.

Due fotoni Imaging di calcio in topi Navigazione una realtà ambiente virtuale

In recent years, two-photon imaging has become an invaluable tool in neuroscience, as it allows for chronic measurement of the activity of genetically ...

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Development of a Virtual Reality Assessment of Everyday Living Skills

Cognitive impairments affect the majority of patients with schizophrenia and these impairments predict poor long term psychosocial outcomes.&#160; Treatment studies aimed at cognitive impairment in patients with schizophrenia not only require demonstration of improvements on cognitive tests, but also evidence that any cognitive changes lead to clinically meaningful improvements.&#160; Measures of &#8220;functional capacity&#8221; index the extent to which individuals have the potential to perform skills required for real world functioning. &#160;Current data do not support the recommendation of any single instrument for measurement of functional capacity.&#160; The Virtual Reality Functional Capacity Assessment Tool (VRFCAT) is a novel, interactive gaming based measure of functional capacity that uses a realistic simulated environment to recreate routine activities of daily living. Studies are currently underway to evaluate and establish the VRFCAT&#8217;s sensitivity, reliability, validity, and practicality.&#160;This new measure of functional capacity is practical, relevant, easy to use, and has several features that improve validity and sensitivity of measurement of function in clinical trials of patients with CNS disorders.

A challenge for proving treatment efficacy for cognitive impairments in schizophrenia is finding the optimizing measurement of skills related to everyday functioning.&#160; The Virtual Reality Functional Capacity Assessment Tool (VRFCAT) is an interactive gaming based computerized measure aimed at skills associated with everyday functioning, including baseline impairments and treatment related changes.

Sviluppo di una Realtà Virtuale valutazione della vita quotidiana Skills

Cognitive impairments affect the majority of patients with schizophrenia and these impairments predict poor long term psychosocial outcomes.&#160; ...

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with schizophrenia who are at familial high risk (FHR) may show similar cognitive and emotional changes. However, the neurological changes underlying the emergence of these symptoms remain unclear. This study sought to identify differences in frontal, striatal, and limbic regions in children and adolescents with FHR using functional magnetic resonance imaging. Groups of 21 children and adolescents at FHR and 21 healthy controls completed an emotional oddball task that relied on selective attention and the suppression of task-irrelevant emotional information. The standard oddball task was modified to include aversive and neutral distractors in order to examine potential group differences in both emotional and executive processing. This task was designed specifically to allow for children and adolescents to complete by keeping the difficulty and emotional image content age-appropriate. Furthermore, we demonstrate a technique for suitable fMRI registration for children and adolescent participants. This paradigm may also be applied in future studies to measure changes in neural activity in other populations with hypothesized developmental changes in executive and emotional processing.

This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR).&#160;FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

Misura di fronto-limbico Attività L&#39;utilizzo di un emotivo Oddball attività nei bambini con familiare ad alto rischio per la schizofrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

A Protocol for Housing Mice in an Enriched Environment

Environmental enrichment (EE) is a housing environment for mice that boosts mental and physical health compared to standard laboratory housing. Our recent studies demonstrate that environmental enrichment decreases adiposity, increases energy expenditure, resists diet induced obesity, and causes cancer remission and inhibition in mice. EE typically consists of larger living space, a variety of &#8216;toys&#8217; to interact with, running wheels, and can include a number of other novel environmental changes. All of this fosters a more complex social engagement, cognitive and physical stimulations. Importantly, the toy location and type of toy is changed regularly, which encourages the mice to adapt to a frequently changing and novel environment. Many variables can be manipulated in EE to promote health effects in mice. Thus these approaches are difficult to control and must be properly managed to successfully replicate the associated phenotypes. Therefore, the goal of this video is to demonstrate how EE is properly set up and maintained to assure a complex, challenging, and controlled environment so that other researchers can easily reproduce the protective effects of EE against obesity and cancer.

Environmental enrichment for mice requires a complex and challenging setup, as well as comprehensive husbandry and handling techniques to assure robust metabolic and anti-cancer effects in the mice. This protocol provides detailed procedures to reproduce the above mentioned effects in mice.

Un protocollo per Mice Housing in un ambiente arricchito

Environmental enrichment (EE) is a housing environment for mice that boosts mental and physical health compared to standard laboratory housing. Our recent ...

A Method to Study Adaptation to Left-Right Reversed Audition

An unusual sensory space is one of the effective tools to uncover the mechanism of adaptability of humans to a novel environment. Although most of the previous studies have used special spectacles with prisms to achieve unusual spaces in the visual domain, a methodology for studying the adaptation to unusual auditory spaces has yet to be fully established. This study proposes a new protocol to set-up, validate, and use a left-right reversed stereophonic system using only wearable devices, and to study the adaptation to left-right reversed audition with the help of neuroimaging. Although individual acoustic characteristics are not yet implemented, and slight spillover of unreversed sounds is relatively uncontrollable, the constructed apparatus shows high performance in a 360&#176; sound source localization coupled with hearing characteristics with little delay. Moreover, it looks like a mobile music player and enables a participant to focus on daily life without arousing curiosity or drawing attention of other individuals. Since the effects of adaptation were successfully detected at the perceptual, behavioral, and neural levels, it is concluded that this protocol provides a promising methodology for studying adaptation to left-right reversed audition, and is an effective tool for uncovering the adaptability of humans to a novel environments in the auditory domain.

The present study proposes a protocol to investigate the adaptation to left-right reversed audition achieved only by wearable devices, using neuroimaging, which can be an effective tool for uncovering the adaptability of humans to a novel environment in the auditory domain.

Un metodo per studiare l'adattamento a sinistra-destra invertita Audition

An unusual sensory space is one of the effective tools to uncover the mechanism of adaptability of humans to a novel environment. Although most of the ...

Measuring the Kinematics of Daily Living Movements with Motion Capture Systems in Virtual Reality

The inability to complete instrumental activities of daily living (IADL) is a precursor to various neuropsychological diseases. Questionnaire-based assessments of IADL are easy to use but prone to subjective bias. Here, we describe a novel virtual reality (VR) test to assess two complex IADL tasks: handling financial transactions and using public transportation. While a participant performs the tasks in a VR setting, a motion capture system traces the position and orientation of the dominant hand and head in a three-dimensional Cartesian coordinate system. Kinematic raw data are collected and converted into &#39;kinematic performance measures,&#39; i.e., motion trajectory, moving distance, and time to completion. Motion trajectory is the path of a particular body part (e.g., dominant hand or head) in space. Moving distance refers to the total distance of the trajectory, and time to completion is how long it took to complete an IADL task. These kinematic measures could discriminate patients with cognitive impairment from healthy controls. The development of this kinematic measuring protocol allows detection of early IADL-related cognitive impairments.

We designed a virtual reality test to assess instrumental activities of daily living (IADL) with a motion capture system. We propose a detailed kinematic analysis to interpret the participant&#39;s various movements, including trajectory, moving distance, and time to completion to evaluate IADL capabilities.

Misura della cinematica dei movimenti di vita quotidiana con sistemi di Motion Capture in realtà virtuale

The inability to complete instrumental activities of daily living (IADL) is a precursor to various neuropsychological diseases. Questionnaire-based ...

Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget

Ethologically relevant behavioral testing is a critical component of any study that uses mouse models to study the cognitive effects of various physiological or pathological changes. The object location task (OLT) and the novel object recognition task (NORT) are two effective behavioral tasks commonly used to reveal the function and relative health of specific brain regions involved in memory. While both of these tests exploit the inherent preference of mice for the novelty to reveal memory for previously encountered objects, the OLT primarily evaluates spatial learning, which relies heavily on hippocampal activity. The NORT, in contrast, evaluates non-spatial learning of object identity, which relies on multiple brain regions. Both tasks require an open-field-testing arena, objects with equivalent intrinsic value to mice, appropriate environmental cues, and video recording equipment and the software. Commercially available systems, while convenient, can be costly. This manuscript details a simple, cost-effective method for building the arenas and setting up the equipment necessary to perform the OLT and NORT. Furthermore, the manuscript describes an efficient testing protocol that incorporates both OLT and NORT and provides typical methods for data acquisition and analysis, as well as representative results. Successful completion of these tests can provide valuable insight into the memory function of various mouse model systems and appraise the underlying neural regions that support these functions.

Here we provide a protocol which includes comprehensive instructions for the economical establishment of murine object location and novel object recognition behavioral testing, including the design, cost, and construction of required equipment as well as execution of behavioral testing, data collection, and analysis.

Riconoscimento di oggetti nuovi e oggetto posizione comportamentali test in topi con un budget limitato

Ethologically relevant behavioral testing is a critical component of any study that uses mouse models to study the cognitive effects of various ...

Impact of High-intensity Interval Exercise and Moderate-Intensity Continuous Exercise on the Cardiac Troponin T Level at an Early Stage of Training

An elevation in cardiac troponin T (cTnT), as a highly specific biomarker of cardiomyocyte damage, after moderate-intensity continuous exercise (MCE) has been described. The exercise-induced cTnT response distorts the diagnostic role of the cTnT assay. Although high-intensity interval exercise (HIE) is growing in popularity and concerns remain about its safety, available data related to cTnT release after HIE is limited, which hampers the use of HIE as a health intervention. Here, we present three representative HIE protocols [traditional HIE (repeated 4 min cycling at 90% V&#775;O2max interspersed with 3 min rest, 200 kJ/session); sprint interval exercise (SIE, repeated 1 min cycling at 120% V&#775;O2max interspersed with 1.5 min rest, 200 kJ/session); and repeated sprint exercise (RSE, 40 x 6 s all-out sprints interspersed with 9 s rest)] and one representative MCE protocol (continuous cycling exercise at an intensity of 60% V&#775;O2max, 200 kJ/session). Forty-seven sedentary, overweight young women were randomly assigned to one of four groups (HIE, SIE, RSE, and MCE). Six bouts of respective exercise were performed by every single group, with each being 48 h apart. Meanwhile, for four groups, the duration of the entire testing period was identical, being 10 days. Before and after the first and final exercise bouts, an assessment was conducted of cTnT. The current study provides a frame of reference giving a clear picture of how a specific exercise session affects the circulating cTnT concentration at the early stage of training. The information may assist with clinical interpretations of post-exercise cTnT elevation and guide the prescription of exercise, especially for HIE.

Here, we present protocols of high-intensity interval and moderate-intensity continuous exercise to observe the response of circulating cardiac troponin T (cTnT) concentration to acute exercise over 10 days. The information may assist with clinical interpretations of post-exercise cTnT elevation and guide the prescription of exercise.

Impatto dell'esercizio a intervalli ad alta intensità e dell'esercizio continuo a intensità moderata sul livello T della Troponina Cardiaca in una fase iniziale dell'allenamento

An elevation in cardiac troponin T (cTnT), as a highly specific biomarker of cardiomyocyte damage, after moderate-intensity continuous exercise (MCE) has ...

Optogenetic Manipulation of Neuronal Activity to Modulate Behavior in Freely Moving Mice

Optogenetic modulation of neuronal circuits in freely moving mice affects acute and long-term behavior. This method is able to perform manipulations of single neurons and region-specific transmitter release, up to whole neuronal circuitries in the central nervous system, and allows the direct measurement of behavioral outcomes. Neurons express optogenetic tools via an injection of viral vectors carrying the DNA of choice, such as Channelrhodopsin2 (ChR2). Light is brought into specific brain regions via chronic optical implants that terminate directly above the target region. After two weeks of recovery and proper tool-expression, mice can be repeatedly used for behavioral tests with optogenetic stimulation of the neurons of interest.
Optogenetic modulation has a high temporal and spatial resolution that can be accomplished with high cell specificity, compared to the commonly used methods such as chemical or electrical stimulation. The light does not harm neuronal tissue and can therefore be used for long-term experiments as well as for multiple behavioral experiments in one mouse. The possibilities of optogenetic tools are nearly unlimited and enable the activation or silencing of whole neurons, or even the manipulation of a specific receptor type by light.
The results of such behavioral experiments with integrated optogenetic stimulation directly visualizes changes in behavior caused by the manipulation. The behavior of the same animal without light stimulation as a baseline is a good control for induced changes. This allows a detailed overview of neuronal types or neurotransmitter systems involved in specific behaviors, such as anxiety. The plasticity of neuronal networks can also be investigated in great detail through long-term stimulation or behavioral observations after optical stimulation. Optogenetics will help to enlighten neuronal signaling in several kinds of neurological diseases.

With optogenetic manipulation of specific neuronal populations or brain regions, behavior can be modified with high temporal and spatial resolution in freely moving animals. By using different optogenetic tools in combination with chronically implanted optical fibers, a variety of neuronal modulations and behavioral testing can be performed.

Manipolazione optogenetica dell'attività neuronale per modulare il comportamento nei topi in movimento libero

Optogenetic modulation of neuronal circuits in freely moving mice affects acute and long-term behavior. This method is able to perform manipulations of ...

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq

To collect dietary intake data in a fast and reliable manner, a flexible and innovative smartphone application (app) called Traqq was developed (iOS/Android). This app can be used as a food record and&#160;24-h recall (or shorter recall periods). Different sampling schemes can be created on either prespecified or random days/times within a predetermined period for both methods, with&#160;push notifications to urge the participants to register their food intake. In case of non-response, notifications are automatically rescheduled to ensure complete data collection. For use as a food record, respondents can access the app and log their food intake throughout the day. Food records close automatically at the end of the day; recalls close after submission of the consumed items. The recall as well as the food record module provide access to an extensive food list based on the Dutch food composition database (FCDB), which can be accustomed to fit different research purposes. When selecting a food item, respondents are simultaneously prompted to insert portion size, i.e., in household measures (e.g., cups, spoons, glasses), standard portion sizes (e.g., small, medium, large), or weight in grams, and eating occasion/time of consumption. Portion size options can be adjusted, e.g., only entry in grams in case of a weighed food record or time of consumption instead of eating occasion). The app also includes a My Dishes function, which allows the respondent to create their own recipes or product combinations (e.g., a daily breakfast) and only report the total quantity consumed. Subsequently, the app accounts for yield and retention factors. The data are stored on a secure server. If desired, additional questions, i.e., in general or those related to specific food items or eating occasions can be incorporated. This paper describes the development of the system (app and backend), including expert evaluations and usability testing.

This article describes the protocol for the development of an innovative smartphone-based dietary assessment application Traqq, including expert evaluations and usability testing.