A systematic review of impairment focussed technology in neurology

References

• GBD 2016 Parkinson’s Disease Collaborators. Global, regional, and national burden of Parkinson’s disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018.
   Web of Science ®Google Scholar
• Lindqvist E, Nygård L, Borell L, et al. Significant junctures on the way towards becoming a user of assistive technology in Alzheimer's disease. Scand J Occup Ther. 2013;20:386–396.
   PubMed Web of Science ®Google Scholar
• Rayegani SM, Raeissadat SA, Sedighipour L, et al. Effect of neurofeedback and electromyographic-biofeedback therapy on improving hand function in stroke patients. Top Stroke Rehabil. 2014;21:137–151.
   PubMed Web of Science ®Google Scholar
• Ma CZH, Zheng YP, Chiu-Chun Lee W. Changes in gait and plantar foot loading upon using vibrotactile wearable biofeedback system in patients with stroke. Top Stroke Rehabil. 2018;25:20–27.
   PubMed Web of Science ®Google Scholar
• Ackerley R, Badre G, Olausson H. Positive effects of a weighted blanket on insomnia. J Sleep Med Disord. 2015;2:1022.
   Google Scholar
• Moher D, Liberati A, Tetzlaff J, et al.; The PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.
   PubMed Web of Science ®Google Scholar
• Center for Evidence-Based Management. Critical appraisal of a survey. [accessed 2019 Jul 30]. Available from: https://www.cebma.org/wp-content/uploads/Critical-Appraisal-Questions-for-a-Cross-Sectional-Study-july-2014.pdf
   Google Scholar
• Critical Appraisal Skills Programme (CASP). [accessed 2019 Jul 30]. Available from: https://casp-uk.net/wp-content/uploads/2018/03/CASP-Qualitative-Checklist-2018_fillable_form.pdf
   Google Scholar
• Jack L, Hayes SC, Scharalda JG Jr, et al. Appraising quantitative research in health education: guidelines for public health educators. Health Promot Pract. 2010;11:161–165.
   PubMedGoogle Scholar
• Pluye P, Robert E, Cargo M, et al. Proposal: a mixed methods appraisal tool for systematic mixed studies reviews. Montreal: McGill University; 2011. [accessed 2019 Jul 30]. Available from: http://mixedmethodsappraisaltool-public.pbworks.com
   Google Scholar
• Gobet F, Chassy P, Bilanlic M. 2011. Foundations of cognitive psychology. New York: McGrawHill Education.
   Google Scholar
• Goldstein S, Naglieri JA. 2014. Handbook of executive functioning. New York: Springer.
   Google Scholar
• Pirogovsky E, Woods SP, Filoteo JV, et al. Prospective memory deficits are associated with poorer everyday functioning in Parkinson’s Disease. J Int Neuropsychol Soc. 2012;18:986–910.
   PubMed Web of Science ®Google Scholar
• Lee DJ, Lee MM, Lee KJ, et al. Asymmetric training using virtual reality reflection equipment and the enhancement of upper limb function in stroke patients: A randomized controlled trial. J Stroke Cerebrovasc Dis. 2014;23:1319–1326.
   PubMed Web of Science ®Google Scholar
• Kandel ER, et al. 2000. Principles of neural science. 4th ed. New York: McGraw-Hill.
   Google Scholar
• Bear MF, Connors BW, Paradiso MA. 2007. Neuroscience: exploring the brain. 3rd ed. Baltimore (MD): Lippincott Williams & Wilkins.
   Google Scholar
• Fearon C, Doherty L, Lynch T. How do i examine rigidity and spasticity? Mov Disord Clin Pract. 2015;2:204–204.
   PubMed Web of Science ®Google Scholar
• Mukherjee A, Chakravarty A. Spasticity mechanisms – for the clinician. Front Neurol. 2010;1:149.
   PubMedGoogle Scholar
• Saposnik G, Teasell R, Mamdani M, et al.; Stroke Outcome Research Canada (SORCan) Working Group. Effectiveness of virtual reality using wii gaming technology in stroke rehabilitation: a pilot randomized clinical trial and proof of principle. Stroke. 2010;41:1477–1484.
   PubMed Web of Science ®Google Scholar
• Carioli J, Teixeira AR. Use of hearing aids and functional capacity in middle-aged and elderly individuals. Int Arch Otorhinolaryngol. 2014;18:249–254.
   PubMedGoogle Scholar
• Popelka GR. 2019. Hearing impairment. New York: McGraw-Hill Education.
   Google Scholar
• Schröter-Morasch H, Ziegler W. Rehabilitation of impaired speech function (dysarthria, dysglossia). GMS Curr Top Otorhinolaryngol Head Neck Surg. 2005;4:15.
   Google Scholar
• Held JP, Klaassen B, van Beijnum BF, et al. Usability evaluation of a VibroTactile feedback system in stroke subjects. Front Bioeng Biotechnol. 2016;4:98.
   PubMed Web of Science ®Google Scholar
• Nauha L, Keränen NS, Kangas M, et al. Assistive technologies at home for people with a memory disorder. Dementia (London). 2018;17:909–923.
   PubMedGoogle Scholar
• Nishiura Y, Nihei M, Nakamura-Thomas H, et al. Effectiveness of using assistive technology for time orientation and memory, in older adults with or without dementia. Disabil Rehabil Assist Technol. 2019.
   PubMedGoogle Scholar
• Lopes P, Pino M, Carletti G, et al. Co-conception process of an innovative assistive device to track and find misplaced everyday objects for older adults with cognitive impairment: the TROUVE project. IRBM. 2016;37:52–57.
   Web of Science ®Google Scholar
• Nguyen BJ, Kim Y, Park K, et al. Improvement in patient-reported quality of life outcomes in severely visually impaired individuals using the aira assistive technology system. Trans Vis Sci Tech. 2018;7:30.
   PubMed Web of Science ®Google Scholar
• Marshall J, Caute A, Chadd K, et al. Technology-enhanced writing therapy for people with aphasia: results of a quasi-randomized waitlist controlled study. Int J Lang Commun Disord. 2019;54:203–220.
   PubMed Web of Science ®Google Scholar
• Adolfsson P, Lindstedt H, Janeslatt G. How people with cognitive disabilities experience electronic planning devices. NeuroRehabilitation. 2015;37:379–392.
   PubMed Web of Science ®Google Scholar
• Bewernitz MW, Mann WC, Dasler P, et al. Feasibility of machine-based prompting to assist persons with dementia. Assist Technol. 2009;21:196–207.
   PubMed Web of Science ®Google Scholar
• Wilson BA, Emslie H, Evans JJ, et al. The NeuroPage system for children and adolescents with neurological deficits. Dev Neurorehabil. 2009;12:421–426.
   PubMed Web of Science ®Google Scholar
• Olsson A, Persson AC, Bartfai A, et al. Sensor technology more than a support. Scand J Occup Ther. 2018;25:79–87.
   PubMed Web of Science ®Google Scholar
• Senjam SS, Foster A, Bascaran C, et al. Assistive technology for students with visual disability in schools for the blind in Delhi. Disabil Rehabil Assist Technol. 2019.
   PubMed Web of Science ®Google Scholar
• Ertzgaard P, Alwin J, Sörbo A, et al. Evaluation of a self-administered transcutaneous electrical stimulation concept for the treatment of spasticity: a randomized placebo-controlled trial. Eur J Phys Rehabil Med. 2018;54:507–517.
   PubMed Web of Science ®Google Scholar
• Jamieson M, Monastra M, Gillies G, et al. The use of a smartwatch as a prompting device for people with acquired brain injury: a single case experimental design study. Neuropsychol Rehabil. 2019;29:513–533.
   PubMed Web of Science ®Google Scholar
• Demers M, Chan Chun Kong D, Levin MF. Feasibility of incorporating functionally relevant virtual rehabilitation in sub-acute stroke care: perception of patients and clinicians. Disabil Rehabil Assist Technol. 2019;14:361–367.
   PubMed Web of Science ®Google Scholar
• Yip BCB, Man DWK. Virtual reality-based prospective memory training program for people with acquired brain injury. NeuroRehabilitation. 2013;32:103–115.
   PubMed Web of Science ®Google Scholar
• Rozental-Iluz C, et al. Improving executive function deficits by playing interactive video-games: Secondary analysis of a randomized controlled trial for individuals with chronic stroke. Eur J Phys Rehabil Med. 2016;52:508–515.
   PubMed Web of Science ®Google Scholar
• Faria AL, Andrade A, Soares L, et al. Benefits of virtual reality based cognitive rehabilitation through simulated activities of daily living: a randomized controlled trial with stroke patients. J NeuroEngineering Rehabil. 2016;13:1–12.
   PubMed Web of Science ®Google Scholar
• Gamito P, Oliveira J, Coelho C, et al. Cognitive training on stroke patients via virtual reality-based serious games. Disabil Rehabil. 2017;39:385–388.
   PubMed Web of Science ®Google Scholar
• Luna-Oliva L, Ortiz-Gutiérrez RM, Cano-de la Cuerda R, et al. Kinect Xbox 360 as a therapeutic modality for children with cerebral palsy in a school environment: a preliminary study. NeuroRehabilitation. 2013;33:513–521.
   PubMed Web of Science ®Google Scholar
• Choi JH, Han EY, Kim BR, et al. Effectiveness of commercial gaming-based virtual reality movement therapy on functional recovery of upper extremity in subacute stroke patients. Ann Rehabil Med. 2014;38:485–493.
   PubMedGoogle Scholar
• GonçAlves GB, Leite M, Orsini M, et al. Effects of using the Nintendo Wii Fit Plus Platform in the sensorimotor training of gait disorders in Parkinson’s disease. Neurol Int. 2014;6:5048.
   PubMedGoogle Scholar
• Jung SM, Choi WH. Effects of virtual reality intervention on upper limb motor function and activity of daily living in patients with lesions in different regions of the brain. J Phys Ther Sci. 2017;29:2103–2106.
   PubMedGoogle Scholar
• Ahmad MA, et al. Virtual reality games as an adjunct in improving upper limb function and general health among stroke survivors. Int J Environ Res Public Health. 2019;16:5144.
   Web of Science ®Google Scholar
• Jacoby M, Averbuch S, Sacher Y, et al. Effectiveness of executive functions training within a virtual supermarket for adults with traumatic brain injury: a pilot study. IEEE Trans Neural Syst Rehabil Eng. 2013;21:182–190.
   PubMed Web of Science ®Google Scholar
• Rohrbach N, Gulde P, Armstrong AR, et al. An augmented reality approach for ADL support in Alzheimer's disease: a crossover trial. J Neuroeng Rehabil. 2019;16:66.
   PubMed Web of Science ®Google Scholar
• Aloise F, Schettini F, Aricò P, et al. P300-based brain-computer interface for environmental control: an asynchronous approach. J Neural Eng. 2011;8:025025.
   PubMed Web of Science ®Google Scholar
• Foldes ST, Taylor DM. Speaking and cognitive distractions during EEG-based brain control of a virtual neuroprosthesis-arm. J NeuroEngineering Rehabil. 2013;10:116.
   PubMed Web of Science ®Google Scholar
• Cox RM, Johnson JA, Xu J. Impact of advanced hearing aid technology on speech understanding for older listeners with mild to moderate, adult-onset, sensorineural hearing Loss. Gerontology. 2014;60:557–568.
   PubMed Web of Science ®Google Scholar
• Höhne J, Holz E, Staiger-Sälzer P, et al. Motor imagery for severely motor-impaired patients: Evidence for brain-computer interfacing as superior control solution. PLoS One. 2014;9:e104854.
   PubMed Web of Science ®Google Scholar
• Tavakolan M, Yong X, Zhang X, et al. Classification scheme for arm motor imagery. J Med Biol Eng. 2016;36:12–21.
   PubMed Web of Science ®Google Scholar
• Zeyl T, Yin E, Keightley M, et al. Adding real-time bayesian ranks to error-related potential scores improves error detection and auto-correction in a P300 speller. IEEE Trans Neural Syst Rehabil Eng. 2016;24:46–56.
   PubMed Web of Science ®Google Scholar
• Zeng H, Wang Y, Wu C, et al. Closed-loop hybrid gaze brain-machine interface based robotic arm control with augmented reality feedback. Front Neurorobot. 2017;11:60.
   PubMed Web of Science ®Google Scholar
• Fall CL, Quevillon F, Blouin M, et al. A multimodal adaptive wireless control interface for people with upper-body disabilities. IEEE Trans Biomed Circuits Syst. 2018;12:564–575.
   PubMed Web of Science ®Google Scholar
• Vuckovic A, Pangaro S, Finda P. Unimanual versus bimanual motor imagery classifiers for assistive and rehabilitative brain computer interfaces. IEEE Trans Neural Syst Rehabil Eng. 2018;26:2407–2415.
   PubMed Web of Science ®Google Scholar
• Remsik AB, Williams L, Gjini K, et al. Ipsilesional Mu rhythm desynchronization and changes in motor behavior following post stroke BCI intervention for motor rehabilitation. Front Neurosci. 2019;13:53.
   PubMed Web of Science ®Google Scholar
• Lancioni GE, O'Reilly MF, Singh NN, et al. Two adults with multiple disabilities use a computer-aided telephone system to make phone calls independently. Res Dev Disabil. 2011;32:2330–2335.
   PubMed Web of Science ®Google Scholar
• Mackenzie L, Bhuta P, Rusten K, et al. Communications technology and motor neuron disease: an Australian Survey of people with motor neuron disease. JMIR Rehabil Assist Technol. 2016;3:e2.
   PubMedGoogle Scholar
• Andreasen Struijk LNS, Bentsen Bo, Gaihede M, et al. Error-free text typing performance of an inductive intra-oral tongue computer interface for severely disabled individuals. IEEE Trans Neural Syst Rehabil Eng. 2017;25:2094–2104.
   PubMed Web of Science ®Google Scholar
• Deemer AD, Swenor BK, Fujiwara K, et al. Preliminary evaluation of two digital image processing strategies for head-mounted magnification for low vision patients. Trans Vis Sci Tech. 2019;8:23.
   PubMed Web of Science ®Google Scholar
• Meza-de-Luna ME, Terven JR, Raducanu B, et al. A Social-Aware Assistant to support individuals with visual impairments during social interaction: a systematic requirements analysis. Int J Hum Comput Stud. 2019;122:50–60.
   Web of Science ®Google Scholar
• Schill O, Wiegand R, Schmitz B, et al. OrthoJacket: an active FES-hybrid orthosis for the paralysed upper extremity. Biomed Tech (Berl). 2011;56:35–44.
   PubMedGoogle Scholar
• Carda S, Biasiucci A, Maesani A, et al. Electrically assisted movement therapy in chronic stroke patients with severe upper limb paresis: a pilot, single-blind, randomized crossover study. Arch Phys Med Rehabil. 2017;98:1628–1635.e2.
   PubMed Web of Science ®Google Scholar
• Brokaw EB, Black I, Holley RJ, et al. Hand Spring Operated Movement Enhancer (HandSOME): a portable, passive hand Exoskeleton for stroke rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2011;19:391–399.
   PubMed Web of Science ®Google Scholar
• Gandolla M, Costa A, Aquilante L, et al. BRIDGE – behavioural reaching interfaces during daily antigravity activities through upper limb exoskeleton: preliminary results. IEEE Int Conf Rehabil Robot. 2017;2017:1007–1012.
   PubMedGoogle Scholar
• Shank TM, Wee J, Ty J, et al. Quantitative measures with WREX usage. IEEE Int Conf Rehabil Robot. 2017;2017:1375–1380.
   PubMedGoogle Scholar
• Xiloyannis M, Cappello L, Binh KD, et al. Preliminary design and control of a soft exosuit for assisting elbow movements and hand grasping in activities of daily living. J Rehabil Assist Technol Eng. 2017;4:2055668316680315.
   Google Scholar
• Sale P, Russo EF, Scarton A, et al. Training for mobility with exoskeleton robot in spinal cord injury patients: a pilot study. Eur J Phys Rehabil Med. 2018;54:745–751.
   PubMed Web of Science ®Google Scholar
• Aubin PM, et al. A pediatric robotic thumb exoskeleton for at-home rehabilitation: the Isolated Orthosis for Thumb Actuation (IOTA). IEEE Int Conf Rehabil Robot, 2013;2013:6650500.
   Google Scholar
• Hall ML, Lobo MA. Design and development of the first exoskeletal garment to enhance arm mobility for children with movement impairments. Assist Technol. 2018;30:251–258.
   PubMed Web of Science ®Google Scholar
• Verros S, Lucassen K, Hekman EEG, et al. Evaluation of intuitive trunk and non-intuitive leg sEMG control interfaces as command input for a 2-D Fitts's law style task. PLoS One. 2019;14:e0214645.
   PubMed Web of Science ®Google Scholar
• Kim JH. The effects of training using EMG biofeedback on stroke patients upper extremity functions. J Phys Ther Sci. 2017;29:1085–1088.
   PubMedGoogle Scholar
• O’Brien EE, Mohtar AA, Diment LE, et al. A detachable electronic device for use with a long white cane to assist with mobility. Assistive Technol. 2014;26:219–226.
   PubMed Web of Science ®Google Scholar
• Vincent C, Routhier F, Martel V, et al. Field testing of two electronic mobility aid devices for persons who are deaf-blind. Disabil Rehabil Assist Technol. 2014;9:414–420.
   PubMedGoogle Scholar
• Gnewikow D, Ricketts T, Bratt GW, et al. Real-world benefit from directional microphone hearing aids. J Rehabil Res Dev. 2009;46:603–618.
   PubMed Web of Science ®Google Scholar
• Lotfi Y, et al. Quality of life improvement in hearing-impaired elderly people after wearing a hearing aid. Arch Iran Med. 2009;12:365–370.
   PubMed Web of Science ®Google Scholar
• Rance G, Corben LA, Du Bourg E, et al. Successful treatment of auditory perceptual disorder in individuals with Friedreich ataxia. Neuroscience. 2010;171:552–555.
   PubMed Web of Science ®Google Scholar
• Anmyr L, Olsson M, Larson K, et al. Children with hearing impairment–living with cochlear implants or hearing aids. Int J Pediatr Otorhinolaryngol. 2011;75:844–849.
   PubMed Web of Science ®Google Scholar
• Abdellaoui A, Tran Ba Huy P. Success and failure factors for hearing-aid prescription: Results of a French national survey. Eur Ann Otorhinolaryngol Head Neck Dis. 2013;130:313–319.
   PubMed Web of Science ®Google Scholar
• Cox RM, Johnson JA, Xu J. Impact of hearing aid technology on outcomes in daily life I: the patients' perspective. Ear Hear. 2016;37:e224–e237.
   PubMed Web of Science ®Google Scholar
• Johnson JA, Xu J, Cox RM. Impact of hearing aid technology on outcomes in Daily Life II: speech understanding and listening effort. Ear Hear. 2016;37:529–540.
   PubMed Web of Science ®Google Scholar
• Johnson JA, Xu J, Cox RM. Impact of hearing aid technology on outcomes in daily life III: localization. Ear Hear. 2017;38:746–759.
   PubMed Web of Science ®Google Scholar
• Verma L, Sanju HK, Scaria B, et al. A comparative study on hearing aid benefits of digital hearing aid use (BTE) from six months to two years. Int Arch Otorhinolaryngol. 2017;21:224–231.
   PubMed Web of Science ®Google Scholar
• Romanet P, Guy M, Allaert FA. Clinical study on the efficacy, acceptance, and safety of hearing aids in patients with mild to moderate presbyacusis. Panminerva Med. 2018;60:92–100.
   PubMed Web of Science ®Google Scholar
• Cuberos-Urbano G, Caracuel A, Valls-Serrano C, et al. A pilot investigation of the potential for incorporating lifelog technology into executive function rehabilitation for enhanced transfer of self-regulation skills to everyday life. Neuropsychol Rehabil. 2018;28:589–601.
   PubMed Web of Science ®Google Scholar
• Heldman DA, Jankovic J, Vaillancourt DE, et al. Essential tremor quantification during activities of daily living. Parkinsonism Relat Disord. 2011;17:537–542.
   PubMed Web of Science ®Google Scholar
• Dalton A, Patel S, Chowdhury AR, et al. Development of a body sensor network to detect motor patterns of epileptic seizures. IEEE Trans Biomed Eng. 2012;59:3204–3211.
   PubMed Web of Science ®Google Scholar
• Poh MZ, Loddenkemper T, Reinsberger C, et al. Convulsive seizure detection using a wrist-worn electrodermal activity and accelerometry biosensor. Epilepsia. 2012;53:e93–e97.
   PubMed Web of Science ®Google Scholar
• Serrano J, Lambrecht S, del Castillo MD, et al. Identification of activities of daily living in tremorous patients using inertial sensors. Expert Syst Appl. 2017;83:40–48.
   Web of Science ®Google Scholar
• Battista L, Romaniello A. A novel device for continuous monitoring of tremor and other motor symptoms. Neurol Sci. 2018;39:1333–1343.
   PubMed Web of Science ®Google Scholar
• Bobin M, Anastassova M, Boukallel M, et al. Design and study of a smart cup for monitoring the arm and hand activity of stroke patients. IEEE J Transl Eng Health Med. 2018;6:1–12.
   Google Scholar
• Hegde N, Zhang T, Uswatte G, et al. The pediatric SmartShoe: wearable sensor system for ambulatory monitoring of physical activity and gait. IEEE Trans Neural Syst Rehabil Eng. 2018;26:477–486.
   PubMed Web of Science ®Google Scholar
• Zheng X, Vieira A, Marcos SL, et al. Activity-aware essential tremor evaluation using deep learning method based on acceleration data. Parkinsonism Relat Disord. 2019;58:17–22.
   PubMed Web of Science ®Google Scholar
• Pierleoni P, Belli A, Bazgir O, et al. A smart inertial system for 24h monitoring and classification of tremor and freezing of gait in Parkinson’s disease. IEEE Sensors J. 2019;19:11612–11623.
   Web of Science ®Google Scholar
• Rowe MA, Kelly A, Horne C, et al. Reducing dangerous nighttime events in persons with dementia by using a nighttime monitoring system. Alzheimers Dement. 2009;5:419–426.
   PubMed Web of Science ®Google Scholar
• Martinez-Sala AS, Losilla F, Sánchez-Aarnoutse JC, et al. Design, implementation and evaluation of an indoor navigation system for visually impaired people. Sensors (Basel). 2015;15:32168–32187.
   PubMed Web of Science ®Google Scholar
• Paladugu DA, Tian Q, Maguluri HB, et al. Towards building an automated system for describing indoor floor maps for individuals with visual impairment. Cyber-Physical Systems. 2015;1:132–159.
   Google Scholar
• Kiuru T, Metso M, Utriainen M, et al. Assistive device for orientation and mobility of the visually impaired based on millimeter wave radar technology—clinical investigation results. Cogent Eng. 2018;5: 1450322.
   Web of Science ®Google Scholar
• Lane H, Rose LE, Woodbrey M, et al. Exploring the effects of using an oral appliance to reduce movement dysfunction in an individual with Parkinson disease: a single-subject design study. J Neurol Phys Ther. 2017;41:52–58.
   PubMed Web of Science ®Google Scholar
• Pröbsting E, Kannenberg A, Zacharias B. Safety and walking ability of KAFO users with the C-Brace® Orthotronic Mobility System, a new microprocessor stance and swing control orthosis. Prosthet Orthot Int. 2017;41:65–77.
   PubMed Web of Science ®Google Scholar
• Laufer Y, Hausdorff JM, Ring H. Effects of a foot drop neuroprosthesis on functional abilities, social participation, and gait velocity. Am J Phys Med Rehabil. 2009;88:14–20.
   PubMed Web of Science ®Google Scholar
• Giorgi RG, Woods RL, Peli E. Clinical and laboratory evaluation of peripheral prism glasses for hemianopia. Optom Vis Sci. 2009;86:492–502.
   PubMed Web of Science ®Google Scholar
• Boman IL, Bartfai A, Borell L, et al. Support in everyday activities with a home-based electronic memory aid for persons with memory impairments. Disabil Rehabil Assist Technol. 2010;5:339–350.
   PubMedGoogle Scholar
• Lindqvist E, Borell L. Computer-based assistive technology and changes in daily living after stroke. Disabil Rehabil Assist Technol. 2012;7:364–371.
   PubMedGoogle Scholar
• Robertson K, Rosasco C, Feuz K, et al. Prompting technologies: a comparison of time-based and context-aware transition-based prompting. Technol Health Care. 2015;23:745–756.
   PubMed Web of Science ®Google Scholar
• Boyd HC, Evans NM, Orpwood RD, et al. Using simple technology to prompt multistep tasks in the home for people with dementia: an exploratory study comparing prompting formats. Dementia (London). 2017;16:424–442.
   PubMedGoogle Scholar
• O'Neill B, Moran K, Gillespie A. Scaffolding rehabilitation behaviour using a voice-mediated assistive technology for cognition. Neuropsychol Rehabil. 2010;20:509–527.
   PubMed Web of Science ®Google Scholar
• O’Neill B, et al. Efficacy of a micro-prompting technology in reducing support needed by people with severe acquired brain injury in activities of daily living: a randomized control trial. J Head Trauma Rehabil. 2018;33:E33–E41.
   PubMed Web of Science ®Google Scholar
• Grigorescu SM, Lüth T, Fragkopoulos C, et al. A BCI-controlled robotic assistant for quadriplegic people in domestic and professional life. Robotica. 2012;30:419–431.
   Web of Science ®Google Scholar
• Wang H, Xu J, Grindle G, et al. Performance evaluation of the Personal Mobility and Manipulation Appliance (PerMMA). Med Eng Phys. 2013;35:1613–1619.
   PubMed Web of Science ®Google Scholar
• Radder B, Prange-Lasonder GB, Kottink A, et al. A wearable soft-robotic glove enables hand support in ADL and rehabilitation: a feasibility study on the assistive functionality. J Rehabil Assist Technol Eng. 2016;3:2055668316670553.
   Google Scholar
• Lee SH, Lee HJ, Chang WH, et al. Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults. J Neuroeng Rehabil. 2017;14:123.
   PubMed Web of Science ®Google Scholar
• Salvietti G, Hussain I, Cioncoloni D, et al. Compensating hand function in chronic stroke patients through the robotic sixth finger. IEEE Trans Neural Syst Rehabil Eng. 2017;25:142–150.
   PubMed Web of Science ®Google Scholar
• Cappello L, Meyer JT, Galloway KC, et al. Assisting hand function after spinal cord injury with a fabric-based soft robotic glove. J NeuroEngineering Rehabil. 2018;15:59.
   PubMed Web of Science ®Google Scholar
• Yurkewich A, Hebert D, Wang RH, et al. Hand extension robot orthosis (HERO) glove: development and testing with stroke survivors with severe hand impairment. IEEE Trans Neural Syst Rehabil Eng. 2019;27:916–926.
   PubMed Web of Science ®Google Scholar
• Kutner NG, Zhang R, Butler AJ, et al. Quality-of-life change associated with robotic-assisted therapy to improve hand motor function in patients with subacute stroke: a randomized clinical trial. Phys Ther. 2010;90:493–504.
   PubMed Web of Science ®Google Scholar
• Lambercy O, Dovat L, Yun H, et al. Effects of a robot-assisted training of grasp and pronation/supination in chronic stroke: a pilot study. J Neuroeng Rehabil. 2011;8:63.
   PubMed Web of Science ®Google Scholar
• Khor KX, Chin PJH, Yeong CF, et al. Portable and reconfigurable wrist robot improves hand function for post-stroke subjects. IEEE Trans Neural Syst Rehabil Eng. 2017;25:1864–1873.
   PubMed Web of Science ®Google Scholar
• Iwamoto Y, Imura T, Suzukawa T, et al. Combination of exoskeletal upper limb robot and occupational therapy improve activities of daily living function in acute stroke patients. J Stroke Cerebrovasc Dis. 2019;28:2018–2025.
   PubMed Web of Science ®Google Scholar
• Onorati F, Regalia G, Caborni C, et al. Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors. Epilepsia. 2017;58:1870–1879.
   PubMed Web of Science ®Google Scholar
• Hendrie WA, Watson MJ, McArthur MA. A pilot mixed methods investigation of the use of Oswestry standing frames in the homes of nine people with severe multiple sclerosis. Disability Rehabil. 2015;37:1178–1185.
   PubMed Web of Science ®Google Scholar
• Maillot P, Perrot A, Hartley A. Effects of interactive physical-activity video-game training on physical and cognitive function in older adults. Psychol Aging. 2012;27:589–600.
   PubMed Web of Science ®Google Scholar
• Grewe P, Kohsik A, Flentge D, et al. Learning real-life cognitive abilities in a novel 360°-virtual reality supermarket: a neuropsychological study of healthy participants and patients with epilepsy. J NeuroEngineering Rehabil. 2013;10:42.
   PubMed Web of Science ®Google Scholar
• Lee KH. Effects of a virtual reality-based exercise program on functional recovery in stroke patients: part 1. J Phys Ther Sci. 2015;27:1637–1640.
   PubMedGoogle Scholar
• Rogers JM, Duckworth J, Middleton S, et al. Elements virtual rehabilitation improves motor, cognitive, and functional outcomes in adult stroke: evidence from a randomized controlled pilot study. J Neuroeng Rehabil. 2019;16:56
   PubMed Web of Science ®Google Scholar
• Liao YY, Tseng HY, Lin YJ, et al. Using virtual reality-based training to improve cognitive function, instrumental activities of daily living and neural efficiency in older adults with mild cognitive impairment: a randomized controlled trial. Eur J Phys Rehabil Med. 2020;56:47–57.
   PubMed Web of Science ®Google Scholar
• McNulty PA, Mouawad MR, Doust CG, et al. Wii-based movement therapy to promote improved upper extremity function post-stroke: a pilot study. J Rehabil Med. 2011;43:527–533.
   PubMed Web of Science ®Google Scholar
• Tanaka T, Kudo A, Sugihara S, et al. A study of upper extremity training for patients with stroke using a virtual environment system. J Phys Ther Sci. 2013;25:575–580.
   PubMedGoogle Scholar
• Winkels DGM, Kottink AIR, Temmink RAJ, et al. Wii™-habilitation of upper extremity function in children with cerebral palsy. an explorative study. Dev Neurorehabil. 2013;16:44–51.
   PubMed Web of Science ®Google Scholar
• Archambault PS, Blackburn É, Reid D, et al. Development and user validation of driving tasks for a power wheelchair simulator. Disabil Rehabil. 2017;39:1549–1556.
   PubMed Web of Science ®Google Scholar
• Vanbellingen T, Filius SJ, Nyffeler T, et al. Usability of videogame-based dexterity training in the early rehabilitation phase of stroke patients: a pilot study. Front Neurol. 2017;8:654.
   PubMed Web of Science ®Google Scholar
• Nissler C, Nowak M, Connan M, et al. VITA-an everyday virtual reality setup for prosthetics and upper-limb rehabilitation. J Neural Eng. 2019;16:026039.
   PubMed Web of Science ®Google Scholar
• Jonsdottir J, Perini G, Ascolese A, et al. Unilateral arm rehabilitation for persons with multiple sclerosis using serious games in a virtual reality approach: Bilateral treatment effect? Mult Scler Relat Disord. 2019;35:76–82.
   PubMed Web of Science ®Google Scholar
• Norouzi-Gheidari N, et al. Feasibility, safety and efficacy of a virtual reality exergame system to supplement upper extremity rehabilitation post-stroke: a pilot randomized clinical trial and proof of principle. Int J Environ Res Public Health. 2019;17:113.
   Web of Science ®Google Scholar
• Giesbrecht EM, Ripat JD, Quanbury AO, et al. Participation in community-based activities of daily living: comparison of a pushrim-activated, power-assisted wheelchair and a power wheelchair. Disabil Rehabil Assist Technol. 2009;4:198–207.
   PubMedGoogle Scholar
• Falk TH, Andrews A, Hotzé F, et al. Evaluation of an ambient noise insensitive hum-based powered wheelchair controller. Disabil Rehabil Assist Technol. 2012;7:242–248.
   PubMedGoogle Scholar
• Boucher P, Atrash A, Kelouwani S, et al. Design and validation of an intelligent wheelchair towards a clinically-functional outcome. J Neuroeng Rehabil. 2013;10:58.
   PubMed Web of Science ®Google Scholar
• Rispin K, Wee J. Comparison between performances of three types of manual wheelchairs often distributed in low-resource settings. Disabil Rehabil Assist Technol. 2015;10:316–322.
   PubMed Web of Science ®Google Scholar
• Amosun S, Ndosi A, Buchanan H. Locally manufactured wheelchairs in Tanzania – are users satisfied? Afr Health Sci. 2016;16:1174–1181.
   PubMed Web of Science ®Google Scholar
• Deems-Dluhy SL, Jayaraman C, Green S, et al. Evaluating the functionality and usability of two novel wheelchair anti-rollback devices for ramp ascent in manual wheelchair users with spinal cord injury. Pm R. 2017;9:483–493.
   PubMedGoogle Scholar