Os autores reconhecem Evan Beisheim, Nicole Capela, Andrew Herbert-Copley de assistência técnica e recolha de dados. O financiamento do projecto foi recebido das Ciências Naturais e Council of Canada (NSERC) Pesquisa de Engenharia e BlackBerry Ltd., incluindo smartphones usados ​​no estudo.

Este protocolo foi aprovado pelo Conselho de Ética em Pesquisa Ottawa Rede de Ciências da Saúde. 1. Preparação <ol><li> Proporcionar aos participantes um resumo da investigação, responder a quaisquer perguntas, e obter o consentimento informado. Características dos participantes de registro (por exemplo, idade, sexo, altura, peso, circunferência da cintura, altura da perna a partir da espinha ilíaca anterior superior ao maléolo medial), código de identificação, data e em uma folha de dados. Certifique-se de que o segundo smartphone que é usada para capturar vídeo está definida para pelo menos 30 quadros por segundo taxa de captura. </li><li> Firmemente anexar um coldre de telefone para cinto ou calça de cintura frontal direito do participante. Inicie o aplicativo de smartphone que será usado para coletar os dados do sensor (ou seja, de registro de dados ou aplicativos WMMS) na medição de smartphones mobilidade e garantir que o aplicativo está sendo executado de forma apropriada. Colocar o smartphone no estojo, com a parte traseira do dispositivo (ca traseiraMera) voltado para fora. </li><li> Iniciar a gravação de vídeo digital em um segundo smartphone. Para anonimato, gravar o vídeo de comparação sem mostrar o rosto da pessoa, mas garantir a gravar todas as transições de atividade. O telefone pode ser de mão. </li></ol> 2. Actividade Circuito <ol><li> Siga o participante e vídeo de suas ações, no segundo smartphone, enquanto eles executam as seguintes ações, ditas pelo investigador: <ol><li> A partir de uma posição de pé, agitar o smartphone para indicar o início do julgamento. </li><li> Continuar em repouso durante pelo menos 10 seg. Esta fase de pé pode ser usado para a calibração orientação telefone 14. </li><li> Caminhe até uma cadeira próxima e se sentar. </li><li> Levante-se e caminhar 60 metros para um elevador. </li><li> Levante-se e esperar o elevador e, em seguida, entrar no elevador. </li><li> Pegue o elevador para o segundo andar. </li><li> Virar e ir para o ambiente doméstico. </li><li> Caminhe até o banheiro e simular escovar os dentes. </li><li> Simule penteando o cabelo. </li><li> Simular a lavagem das mãos. </li><li> Seque as mãos com uma toalha. </li><li> Caminhe até a cozinha. </li><li> Tome pratos de um rack e coloque-os sobre o balcão. </li><li> Encha uma chaleira com água da pia da cozinha. </li><li> Coloque a chaleira no fogão elemento. </li><li> Coloque o pão em uma torradeira. </li><li> Caminhe até a sala de jantar. </li><li> Sente-se em uma mesa da sala de jantar. </li><li> Simular uma refeição à mesa. </li><li> Levante-se e caminhar de volta para a pia da cozinha. </li><li> Enxaguar os pratos e colocá-los em um rack. </li><li> A pé da cozinha de volta ao elevador. </li><li> Levante-se e esperar o elevador e, em seguida, entrar no elevador. </li><li> Pegue o elevador para o primeiro andar. </li><li> Andar 50 metros a uma escada. </li><li> Abra a porta e entrar na escada. </li><li> Subir escadas (13 passos, cerca de pouso, 13 passos). </li><li> Abra a porta da escada para o corredor. </li><li> Vire à direita e andar pelo corredor por 15 metros. </li><li> Vire-se e andar 15 metros de volta para a escada. </li><li> Abra a porta e entrar na escada. </li><li> Descer as escadas (13 passos, cerca de pouso, 13 passos). </li><li> Saia da escada e entra em uma sala. </li><li> Deite-se de uma cama. </li><li> Levante-se e caminhar 10 metros para uma rampa. </li><li> Caminhe até a rampa, vire-se, em seguida, descer a rampa (20 metros). </li><li> Continue caminhando para o corredor e abrir a porta para fora. </li><li> Caminhe 100 metros da via pavimentada. </li><li> Vire-se e caminhar de volta para o quarto. </li><li> Entra na sala e ficar no ponto de partida. </li><li> Continuar de pé, e, em seguida, agitar o smartphone para indicar o fim do julgamento. </li></ol></li></ol> 3. Teste de Conclusão <ol><li> Parar a gravação de vídeo do smartphone e pedir ao participante para remover e retornar o smartphone e coldre. Parar o log de dados ou aplicação WMMS na smartphone. Copie os arquivos de dados de movimento adquiridos e do arquivo de vídeo de ambos os telefones a um computador para o pós-processamento. </li></ol> 4. Pós-processamento <ol><li> Sincronizar tempo entre o vídeo e os dados do sensor cru, determinando o tempo quando a ação começou trepidação. Este movimento de agitação corresponde a um sinal acelerômetro e vídeo moldura distinto. Verifique se há erro de sincronização subtraindo a hora de agitação de final do tempo shake de início, para fontes de dados de sensores e vídeo. As diferenças de tempo deve ser semelhante entre os dois conjuntos de dados. </li><li> Determine os tempos reais de mudança de estado do vídeo padrão-ouro, registrando a diferença de tempo a partir do momento shake de começo para o quadro de vídeo na transição entre atividades. Use software de edição de vídeo para obter tempo para dentro de 0,033 sec (ou seja, 30 quadros por segundo taxa de vídeo). Use software WMMS para gerar mudanças de estado comparáveis ​​a partir dos dados do sensor. </li><li> Gerar dois conjuntos de dados, umcom atividades verdadeiras e o segundo com actividades previstas, por marcação da actividade para cada quadro de vídeo (com base na mudança de estado de sincronismo) e calculando em seguida a actividade prevista, em cada tempo de quadro de vídeo a partir da saída WMMS. Para avaliação de desempenho WMMS, calcular verdadeiros positivos, falsos negativos, verdadeiros negativos, falsos positivos entre a atividade padrão-ouro e WMMS previu atividade. Use esses parâmetros para calcular medidas de desfechos sensibilidade, especificidade, e F-score. Nota: A definição de tolerância de 3 janelas de dados de cada lado da janela que está sendo analisado pode ser usado para determinar os resultados de mudança de estado, e 2 janelas de dados para os resultados de classificação. Por exemplo, desde 1 segundo janelas de dados foram utilizados para a WMMS neste estudo, 3 seg antes e depois da janela de corrente foram examinados de modo a que as alterações consecutivos dentro desta tolerância são ignorados. A consideração foi que as mudanças de estado que acontecem em menos de 3 segundos pode ser ignorado para huma brutaanálise de movimento n uma vez que estes estados seria considerado transitório. </li></ol>

<ol>
	<li>Lara, O. D., Labrador, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Survey+on+Human+Activity+Recognition+using+Wearable+Sensors.">A Survey on Human Activity Recognition using Wearable Sensors.</a> IEEE Communications Surveys Tutorials. 15 (3), 1192-1209 (2013).</li><li>Foerster, F., Smeja, M., Fahrenberg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+of+posture+and+motion+by+accelerometry:+a+validation+study+in+ambulatory+monitoring.">Detection of posture and motion by accelerometry: a validation study in ambulatory monitoring.</a> Computers in Human Behavior. 15 (5), 571-583 (1999).</li><li>Elsmore, T. F., Naitoh, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Monitoring Activity With a Wrist-Worn Actigraph: Effects of Amplifier Passband and threshold Variations. , (1993).</li><li>Kripke, D. F., Webster, J. B., Mullaney, D. J., Messin, S., Mason, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Measuring sleep by wrist actigraph. , (1981).</li><li>Lockhart, J. W., Pulickal, T., Weiss, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Applications+of+mobile+activity+recognition.">Applications of mobile activity recognition.</a> Proceedings of the 2012 ACM Conference on Ubiquitous Computing. , 1054-1058 (2012).</li><li>Incel, O. D., Kose, M., Ersoy, C. <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+and+Taxonomy+of+Activity+Recognition+on+Mobile+Phones.">A Review and Taxonomy of Activity Recognition on Mobile Phones.</a> BioNanoScience. 3 (2), 145-171 (2013).</li><li>Yang, C. C., Hsu, Y. 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. D., Baddour, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mobility+change-of-state+detection+using+a+smartphone-based+approach.">Mobility change-of-state detection using a smartphone-based approach.</a> IEEE International Workshop on Medical Measurements and Applications Proceedings (MeMeA). , 43-46 (2010).</li><li>Wu, H. H., Lemaire, E. D., Baddour, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Change-of-state+determination+to+recognize+mobility+activities+using+a+BlackBerry+smartphone.">Change-of-state determination to recognize mobility activities using a BlackBerry smartphone.</a> , 5252-5255 (2011).</li><li>Wu, H., Lemaire, E. D., Baddour, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Activity+Change-of-state+Identification+Using+a+Blackberry+Smartphone.">Activity Change-of-state Identification Using a Blackberry Smartphone.</a> Journal of Medical and Biological Engineering. 32 (4), 265-271 (2012).</li><li>Tundo, M. D., Lemaire, E., Baddour, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correcting+Smartphone+orientation+for+accelerometer-based+analysis.">Correcting Smartphone orientation for accelerometer-based analysis.</a> IEEE International Symposium on Medical Measurements and Applications Proceedings (MeMeA). , 58-62 (2013).</li><li>Tundo, M. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Development of a human activity recognition system using inertial measurement unit sensors on a smartphone. , (2014).</li></ol>

The authors declare that they have no competing financial interests.

Reconhecimento atividade humana com um sistema de monitoramento de mobilidade wearable tem recebido mais atenção nos últimos anos devido aos avanços técnicos em computação e smartphones wearable e necessidades sistemáticas para medidas de resultados quantitativos que ajudam na tomada de decisão clínica e avaliação de intervenção em saúde. A metodologia descrita neste trabalho foi eficaz para avaliar o desenvolvimento WMMS desde foram encontrados erros de classificação de atividade que não estaria prese...

Sensoriamento Ubiquitous tornou-se uma área de pesquisa de contrato devido à cada vez mais poderosos,, computação de baixo custo pequeno e equipamento de um sensor. Monitoramento mobilidade usando sensores portáteis tem gerado um grande interesse desde a microeletrônica do consumidor-nível são capazes de detectar características de movimento com alta precisão 1. Reconhecimento atividade humana (HAR) usando sensores portáteis é uma área recente da pesquisa, com estudos preliminares realizados na década de 1980 e 1990 2-4. Smartphones modernos contêm os sensores necessários e capacidade de computação em tempo real para o reconhecimento actividade de mobilidade. Análise em tempo real no dispositivo permite a classificação de atividades e fazer o upload de dados sem intervenção do usuário ou investigador. Um smartphone com software de análise de mobilidade poderia fornecer rastreamento de fitness, vigilância da saúde, queda de detecção, em casa ou trabalho de automação e auto-gestão exercise programas 5. Smartphones podem ser considerados plataformas de medição inercial para a detecção de actividades móveis e padrões móveis em humanos, usando recursos de sinais matemáticos gerados calculados com saídas de sensores a bordo 6. Métodos de geração de recursos comuns incluem heurística, no domínio do tempo, no domínio da freqüência, e wavelet abordagens baseadas em análise 7. Sistemas de smartphones HAR modernos têm mostrado altas precisões de previsão ao detectar atividades especificadas 1,5,6,7. Esses estudos variam em metodologia de avaliação, bem como a precisão pois a maioria dos estudos tem seu próprio conjunto de treinamento, configuração ambiental, e protocolo de coleta de dados. A sensibilidade, especificidade, precisão, recall, precisão, e F-Score são comumente usados ​​para descrever a qualidade de previsão. No entanto, pouca ou nenhuma informação está disponível sobre os métodos de reconhecimento &quot;atividade concorrente&quot; e avaliação da capacidade de detectar mudanças de atividade em tempo real1, para sistemas de HAR que tentam categorizar diversas atividades. Métodos de avaliação para a precisão do sistema HAR variar substancialmente entre os estudos. Independentemente do algoritmo de classificação ou recursos aplicados, descrições de métodos de avaliação padrão ouro são vago para a maioria das pesquisas HAR. Reconhecimento atividade em um ambiente de vida diária não tem sido extensivamente pesquisada. A maioria dos sistemas de reconhecimento de actividade à base de smartphones são avaliados de uma forma controlada, conduzindo a um protocolo de avaliação que pode ser vantajoso para o algoritmo em vez de realista para um ambiente do mundo real. Dentro de seu esquema de avaliação, os participantes muitas vezes executar apenas as ações pretendidas para a previsão, em vez de aplicar uma grande variedade de actividades realista para o participante para executar consecutivamente, imitando os eventos da vida real. Alguns HAR smartphones estuda 8,9 grupo actividades semelhantes em conjunto, tais como escadas e caminhar, Mas excluem outras atividades a partir do conjunto de dados. Precisão da previsão é então determinado pela forma como o algoritmo identificou as atividades-alvo. Dernbach et al. 9 teve participantes escrever a atividade que eles estavam prestes a executar antes de se mudar, interrompendo transições contínuas de mudança de estado. Avaliações de sistemas de HAR devem avaliar o algoritmo enquanto o participante realiza ações naturais em um ambiente vida diária. Isso permitiria uma avaliação da vida real que replica o uso diário do pedido. Um circuito realista inclui muitas mudanças de estado, bem como uma combinação de acções não previsíveis pelo sistema. Um investigador pode então avaliar a resposta do algoritmo para esses movimentos adicionais, avaliando assim a robustez do algoritmo para movimentos anômalos. Este trabalho apresenta um protocolo de avaliação Sistema de Monitoramento de Mobilidade Wearable (WMMS) que usa um campo controlado que reflete na vida real ambientes de vida diárias. WMMSavaliação pode então ser feita sob condições controladas, mas realistas. Neste protocolo, usamos uma WMMS de terceira geração que foi desenvolvido na Universidade de Ottawa e Ottawa Hospital Research Institute 11-15. O WMMS foi projetado para smartphones com um acelerômetro tri-eixo e giroscópio. O algoritmo de mobilidade representa variabilidade de utilizador, proporciona a redução do número de falsos positivos para a identificação de alterações de estado, e aumenta a sensibilidade na categorização actividade. Minimizando falsos positivos é importante uma vez que o WMMS dispara a gravação do clipe de vídeo curto quando são detectadas mudanças de estado de atividade, para avaliação da atividade sensível ao contexto que melhora ainda mais a classificação WMMS. Gravação de vídeo desnecessário cria ineficiências no armazenamento e uso da bateria. O algoritmo WMMS é estruturado como um modelo de baixo computacional aprendizagem e avaliada utilizando diferentes níveis de previsão, onde um aumento no nível de previsão significa um aumento na quantidadeações de reconhecível.

<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.

O protocolo do estudo foi realizado com uma amostra de conveniência de quinze participantes sãos cuja média de peso foi de 68,9 (± 11,1) kg, altura era de 173,9 (± 11,4) cm, ea idade foi de 26 (± 9) anos, recrutados a partir do Hospital de Ottawa e Universidade de Ottawa equipe e alunos. Um smartphone capturado dados do sensor a uma taxa de 40-50 Hz variável. Variações da taxa de amostra são típicos para a amostragem do sensor smartphone. Um segundo aparelho foi usado para gravar vídeo digital em 1280x720 (7...

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.

Avaliação de um Sistema de Reconhecimento de Atividade Humana baseado em Smartphone em uma Vida Diária Ambiente

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

Research

JoVE Journal

Behavior

8.8K visualizações.  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.

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

Construction of Microdrive Arrays for Chronic Neural Recordings in Awake Behaving Mice

State-of-the-art electrophysiological recordings from the brains of freely behaving animals allow researchers to simultaneously examine local field potentials (LFPs) from populations of neurons and action potentials from individual cells, as the animal engages in experimentally relevant tasks. Chronically implanted microdrives allow for brain recordings to last over periods of several weeks. Miniaturized drives and lightweight components allow for these long-term recordings to occur in small mammals, such as mice. By using tetrodes, which consist of tightly braided bundles of four electrodes in which each wire has a diameter of 12.5 &mu;m, it is possible to isolate physiologically active neurons in superficial brain regions such as the cerebral cortex, dorsal hippocampus, and subiculum, as well as deeper regions such as the striatum and the amygdala. Moreover, this technique insures stable, high-fidelity neural recordings as the animal is challenged with a variety of behavioral tasks. This manuscript describes several techniques that have been optimized to record from the mouse brain. First, we show how to fabricate tetrodes, load them into driveable tubes, and gold-plate their tips in order to reduce their impedance from M&Omega; to K&Omega; range. Second, we show how to construct a custom microdrive assembly for carrying and moving the tetrodes vertically, with the use of inexpensive materials. Third, we show the steps for assembling a commercially available microdrive (Neuralynx VersaDrive) that is designed to carry independently movable tetrodes. Finally, we present representative results of local field potentials and single-unit signals obtained in the dorsal subiculum of mice. These techniques can be easily modified to accommodate different types of electrode arrays and recording schemes in the mouse brain.

The design and assembly of microdrives for in vivo electrophysiological recordings of brain signals from the mouse is described. By attaching microelectrode bundles to sturdy driveable carriers, these techniques allow for long-term and stable neural recordings. The lightweight design allows for unrestricted behavioral performance by the animal following drive implantation.

Construção de Matrizes Microdrive para gravações Neurais crônica na Awake Mice comportam

State-of-the-art electrophysiological recordings from the brains of freely behaving animals allow researchers to simultaneously examine local field ...

Comportamento

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.

Dois fótons de imagem de cálcio em camundongos Navegando um ambiente da realidade virtual

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

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.

Desenvolvimento de uma Avaliação de Realidade Virtual do cotidiano Habilidades de Vida

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

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.

Um protocolo para alojar ratos em um ambiente enriquecido

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.

Um método para estudar a adaptação para a esquerda-direita invertida audição

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 ...

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers

Reciprocal social behavior (RSB), an early-emerging capacity to engage in social contingency&#8212;which is foundational for both social learning and social competency&#8212;is hypothesized to be disrupted in autism spectrum disorder (ASD). The ability to quantify the full range of RSB during the toddler period, when core symptoms of ASD often arise, is pivotal for evaluating early risk for ASD, characterizing social development, and tracking response to early interventions. However, important parameters of variation in RSB&#8212;especially prior to the development of verbal language&#8212;can be nuanced and difficult to characterize using questionnaire-based methods. To address this challenge, we developed a system for measuring quantitative variation in RSB in toddlers (ages 18 - 30 months) that incorporated not only standard questionnaire data from caregivers but also a novel set of video-referenced items, through which a respondent compares the behavior of a subject to that observed in a short video of a young child manifesting a highly competent level of social communication. Testing of this measure in a general population sample of twins confirmed that both the video-referenced items and the RSB Total Score (video-referenced items plus non-video-referenced items) displayed unimodal, continuous distributions, strong internal consistency, marked preservation of individual differences, and extremely high heritability. In addition, video-referenced items were particularly sensitive to quantifying incremental changes in social communication, a major element of RSB, over the course of early childhood development. Scores on the vrRSB clearly differentiated children with and without ASD and these data comprise an initial validation of this promising method for quantifying early RSB&#8212;cross-sectionally, over time, and as a function of early intervention.

Here we present a protocol for administration of the video-referenced rating of reciprocal social behavior (vrRSB) using a paper or online version. This survey quantifies RSB, a prerequisite for social competence, in toddlers through &#34;video-referenced&#34; items whereby a subject is compared to a reference child shown in a three-minute video.

Utilização de um vídeo marcador de âncora para rápida avaliação Serial de Comunicação Social nas crianças

Reciprocal social behavior (RSB), an early-emerging capacity to engage in social contingency&#8212;which is foundational for both social learning and ...

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.

Medir a cinemática dos movimentos de vida diária com sistemas de captura de movimento em realidade Virtual

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.

Reconhecimento de objetos novos e localização de objeto comportamental testes em ratos em um orçamento

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.

Impacto do exercício intervalado de alta intensidade e do exercício contínuo de intensidade moderada no nível de troponina cardíaca T em estágio inicial de treinamento

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.

Manipulação optogenética da atividade neuronal para modular o comportamento em camundongos em movimento livre

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