Robotic Cane as a Soft SuperLimb for Elderly Sit-to-Stand Assistance*
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Xia Wu | Ziqi Liu | Haiyuan Liu | Fang Wan | Chenglong Fu | Harry Asada | Zheng Wang | Chaoyang Song | Mingdong Chen | Chaoyang Song | Chenglong Fu | Z. Wang | Ming-Shui Chen | Fang Wan | Haiyuan Liu | Harry Asada | Xia Wu | Ziqi Liu
[1] Olivier Beauchet,et al. Timed up and go test and risk of falls in older adults: A systematic review , 2011, The journal of nutrition, health & aging.
[2] W. Leslie,et al. Preventing falls in elderly persons. , 2003, The New England journal of medicine.
[3] M. Tinetti. Clinical practice. Preventing falls in elderly persons. , 2003, The New England journal of medicine.
[4] Nasser Kehtarnavaz,et al. A survey of depth and inertial sensor fusion for human action recognition , 2015, Multimedia Tools and Applications.
[5] M. Laplante,et al. MOBILITY DEVICE USE IN THE UNITED STATES: DISABILITY STATISTICS REPORT , 2000 .
[6] Paul J. M. Havinga,et al. Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey , 2010, ARCS Workshops.
[7] Marco La Cascia,et al. 3D skeleton-based human action classification: A survey , 2016, Pattern Recognit..
[8] P. Riley,et al. Sit to stand from progressively lower seat heights -- alterations in angular velocity. , 1996, Clinical biomechanics.
[9] B Isaacs,et al. Clinical and laboratory studies of falls in old people. Prospects for prevention. , 1985, Clinics in geriatric medicine.
[10] C. Ogden,et al. Mean Body Weight, Height, Waist Circumference, and Body Mass Index Among Adults: United States, 1999-2000 Through 2015-2016. , 2018, National health statistics reports.
[11] Max Mignotte,et al. Fall Detection from Depth Map Video Sequences , 2011, ICOST.
[12] B. Weiner,et al. The shaping of individual meanings assigned to assistive technology: a review of personal factors , 2002, Disability and rehabilitation.
[13] Takayoshi Yamada,et al. Relationships between ground reaction force parameters during a sit-to-stand movement and physical activity and falling risk of the elderly and a comparison of the movement characteristics between the young and the elderly. , 2009, Archives of gerontology and geriatrics.
[14] Sara M. Bradley,et al. Geriatric assistive devices. , 2011, American family physician.
[15] P. Leva. Adjustments to Zatsiorsky-Seluyanov's segment inertia parameters. , 1996 .
[16] Tae-Gyung Kang,et al. Mobility Device Use in the United States , 2003 .
[17] J. Broekens,et al. Assistive social robots in elderly care: a review , 2009 .
[18] G. Pyka,et al. Effect of muscle strength and movement speed on the biomechanics of rising from a chair in healthy elderly and young women. , 1998, Gait & posture.
[19] Miguel López-Coronado,et al. Social Robots for People with Aging and Dementia: A Systematic Review of Literature. , 2019, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.
[20] M Crivellini,et al. Biomechanical analysis of sit-to-stand movement in normal and obese subjects. , 2003, Clinical biomechanics.
[21] Baharak Shakeri Aski,et al. Intelligent video surveillance for monitoring fall detection of elderly in home environments , 2008, 2008 11th International Conference on Computer and Information Technology.
[22] Chris A McGibbon,et al. Chair rise strategies in older adults with functional limitations. , 2007, Journal of rehabilitation research and development.
[23] Takayoshi Yamada,et al. Instruction in Reliability and Magnitude of Evaluation Parameters at Each Phase of a Sit-to-Stand Movement , 2005, Perceptual and motor skills.
[24] H. Harry Asada,et al. Design of Extra Robotic Legs for Augmenting Human Payload Capabilities by Exploiting Singularity and Torque Redistribution , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[25] M A Hughes,et al. Chair rise strategies in the elderly. , 1994, Clinical biomechanics.
[26] H. Harry Asada,et al. Hybrid Open-Loop Closed-Loop Control of Coupled Human–Robot Balance During Assisted Stance Transition With Extra Robotic Legs , 2019, IEEE Robotics and Automation Letters.
[27] Li Fei-Fei,et al. 3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities , 2018, MLHC.
[28] G. M. Shambes,et al. Biomechanical analysis of the sit-to-stand motion in elderly persons. , 1992, Archives of physical medicine and rehabilitation.
[29] Andrew W. Fitzgibbon,et al. Real-time human pose recognition in parts from single depth images , 2011, CVPR 2011.
[30] H. Harry Asada,et al. Independent, voluntary control of extra robotic limbs , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[31] Diane Podsiadlo,et al. The Timed “Up & Go”: A Test of Basic Functional Mobility for Frail Elderly Persons , 1991, Journal of the American Geriatrics Society.
[32] Nikolaos G. Bourbakis,et al. A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[33] Alexandre Alahi,et al. A computer vision system for deep learning-based detection of patient mobilization activities in the ICU , 2019, npj Digital Medicine.