Mobile inertial sensors for fall risk screening and prediction (2017)
- Authors:
- Autor USP: PONTI, MOACIR ANTONELLI - ICMC
- Unidade: ICMC
- Subjects: TECNOLOGIAS DA SAÚDE; PROCESSAMENTO DE SINAIS; IDOSOS
- Language: Inglês
- Imprenta:
- Publisher: HC,FMRP,USP
- Publisher place: Ribeirão Preto
- Date published: 2017
- Source:
- Conference titles: Congresso Brasileiro de Gerontecnologia
-
ABNT
BET, P e CASTRO, P. C e PONTI, Moacir Antonelli. Mobile inertial sensors for fall risk screening and prediction. Medicina. Ribeirão Preto: HC,FMRP,USP. Disponível em: http://revista.fmrp.usp.br/2017/suplementos/vol%2050%20supl%203-%20Suplemento%20Gerontec%202017.pdf. Acesso em: 19 abr. 2024. , 2017 -
APA
Bet, P., Castro, P. C., & Ponti, M. A. (2017). Mobile inertial sensors for fall risk screening and prediction. Medicina. Ribeirão Preto: HC,FMRP,USP. Recuperado de http://revista.fmrp.usp.br/2017/suplementos/vol%2050%20supl%203-%20Suplemento%20Gerontec%202017.pdf -
NLM
Bet P, Castro PC, Ponti MA. Mobile inertial sensors for fall risk screening and prediction [Internet]. Medicina. 2017 ; 50 31-35.[citado 2024 abr. 19 ] Available from: http://revista.fmrp.usp.br/2017/suplementos/vol%2050%20supl%203-%20Suplemento%20Gerontec%202017.pdf -
Vancouver
Bet P, Castro PC, Ponti MA. Mobile inertial sensors for fall risk screening and prediction [Internet]. Medicina. 2017 ; 50 31-35.[citado 2024 abr. 19 ] Available from: http://revista.fmrp.usp.br/2017/suplementos/vol%2050%20supl%203-%20Suplemento%20Gerontec%202017.pdf - Does background intensity estimation influence the iterative restoration of microscope images?
- Combining classifiers: from the creation of ensembles to the decision fusion
- Three-dimensional noisy image restoration using filtered extrapolation and deconvolution
- Partially supervised anomaly detection using convex hulls on a 2D parameter space
- One-class to multi-class model update using the class-incremental optimum-path forest classifier
- Extração de atributos visuais compactos para reconhecimento de padrões visuais em dispositivos móveis
- Deep convolutional neural networks and noisy images
- Robust feature spaces from pre-trained deep network layers for skin lesion classification
- Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections
- Fall detection and fall risk assessment in older person using wearable sensors: a systematic review
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
