Validation of noninvasive body sensor network technology in the detection of agitation in dementia
Open accessAbstract
OBJECTIVE: Agitated behaviors are one of the most frequent reasons that patients with dementia are placed in long-term care settings. This study aims to validate the ability of a custom Body Sensor Network (BSN) to capture the presence of agitation against currently accepted subjective measures, the Cohen-Mansfield Agitation Inventory (CMAI) and the Aggressive Behavior Scale (ABS) and to discriminate between agitation and cognitive decline. METHODS: Six patients identified as being at high risk for agitated behaviors were enrolled in this study. The devices were applied at three sites for three hours while behaviors were annotated simultaneously and subsequently repeated twice for each enrolled subject. RESULTS: We found that the BSN was a valid measure of agitation based on construct validity testing and secondary validation using non-parametric ANOVAs. DISCUSSION: The BSN shows promise from these pilot results. Further testing with a larger sample is needed to replicate these results.
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ICT can be used for the assessment of agitation.
“ICT can be used for the assessment of agitation, one of the most challenging symptoms to manage for caregivers (286, 287).”
From The Multidisciplinary Approach to Alzheimer’s Disease and Dementia. A Narrative Review of Non-Pharmacological Treatment (2018) · cites this paper as [287]
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Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282 · see citing works
Hirono, N., Mori, E., Ikejiri, Y., Imamura, T., Shimomura, T., Hashimoto, M., Yamashita, H., & Ikeda, M. (1997) · PubMed · Cited by 21,010 · see citing works
Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589 · see citing works
Older Adults' Reasons for Using Technology while Aging in Place
Peek, S. T. M., Luijkx, K. G., Rijnaard, M. D., Nieboer, M. E., van der Voort, C. S., Aarts, S., van Hoof, J., Vrijhoef, H. J., & Wouters, E. (2015) · Gerontology · doi:10.1159/000430949 · Cited by 19,803 · see citing works
Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly
Kangas, M., Korpelainen, R., Vikman, I., Nyberg, L., & Jämsä, T. J. (2014) · Gerontology · doi:10.1159/000362720 · Cited by 19,003 · see citing works
Convergent and discriminant validation by the multitrait-multimethod matrix.
Campbell, D. T., & Fiske, D. W. (1959) · Psychological Bulletin · doi:10.1037/h0046016 · Cited by 17,116 · see citing works
A Description of Agitation in a Nursing Home
Cohen-mansfield, J., Marx, M. S., & Rosenthal, A. S. (1989) · Journal of Gerontology · doi:10.1093/geronj/44.3.m77 · Cited by 1,349 · see citing works
On a simple algorithm to calculate the 'energy' of a signal
Kaiser, J. F. (2002) · International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1990.115702 · Cited by 1,172 · see citing works
Psychiatric symptoms and nursing home placement of patients with Alzheimer's disease
(1990) · American Journal of Psychiatry · doi:10.1176/ajp.147.8.1049 · Cited by 744 · see citing works
Point and 5‐year period prevalence of neuropsychiatric symptoms in dementia: the Cache County Study
Steinberg, M., Shao, H., Zandi, P. P., Lyketsos, C. G., Welsh-Bohmer, K. A., Norton, M. C., Breitner, J. C. S., Steffens, D. C., & Tschanz, J. T. (2007) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1858 · Cited by 743 · see citing works
Chenoweth, L., King, M. T., Jeon, Y.-H., Brodaty, H., Stein-Parbury, J., Norman, R., Haas, M., & Luscombe, G. (2009) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70045-6 · Cited by 528 · see citing works
Fossey, J., Ballard, C. G., Juszczak, E., James, I. A., Alder, N. C., Jacoby, R. J., & Howard, R. J. (2006) · BMJ · doi:10.1136/bmj.38782.575868.7c · Cited by 512 · see citing works
Bharucha, A. J., Anand, V. R., Forlizzi, J., Dew, M. A., Reynolds, C. F., Stevens, S., & Wactlar, H. D. (2008) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e318187dde5 · Cited by 350 · see citing works
Sloane, P. D., Hoeffer, B., Mitchell, C. M., McKenzie, D. A., Barrick, A. L., Rader, J., Stewart, B. J., Talerico, K. A., Rasin, J. H., Zink, R. C., et al. (2004) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2004.52501.x · Cited by 311 · see citing works
Buhr, G., Kuchibhatla, M., & Clipp, E. (2006) · The gerontologist · doi:10.1093/geront/46.1.52 · Cited by 280 · see citing works
Cohen‐Mansfield, J., Libin, A., & Marx, M. S. (2007) · The Journals of Gerontology Series A · doi:10.1093/gerona/62.8.908 · Cited by 257 · see citing works
Incidence of and risk factors for hallucinations and delusions in patients with probable AD
Paulsen, J. S., Salmon, D. P., Thal, L. J., Romero, R., Weisstein–Jenkins, C., Galasko, D., Hofstetter, C. R., Thomas, R., Grant, I., & Jeste, D. V. (2000) · Neurology · doi:10.1212/wnl.54.10.1965 · Cited by 254 · see citing works
The Aggressive Behavior Scale: A New Scale to Measure Aggression Based on the Minimum Data Set
Perlman, C. M., & Hirdes, J. P. (2008) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2008.02048.x · Cited by 253 · see citing works
Elderly Patients With Dementia-Related Symptoms of Severe Agitation and Aggression
Salzman, C., Jeste, D. V., Meyer, R. E., Cohen‐Mansfield, J., Cummings, J. L., Grossberg, G. T., Jarvick, L., KRAEMER, H. C., Lebowitz, B. D., Maslow, K., et al. (2008) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v69n0602 · Cited by 229 · see citing works
Cohen-Mansfield, J. (1997) · International Psychogeriatrics · doi:10.1017/s1041610297003530 · Cited by 196 · see citing works
An observational study of agitation in agitated nursing home residents
Cohen-Mansfield, J., Werner, P., & Marx, M. S. (1989) · International Psychogeriatrics · doi:10.1017/s1041610289000165 · Cited by 163 · see citing works
Ballard, C. G., Margallo‐Lana, M., Fossey, J., Reichelt, K., Myint, P., Potkins, D., & O'Brien, J. T. (2001) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v62n0810 · Cited by 161 · see citing works
Utilization of Self-Identity Roles for Designing Interventions for Persons With Dementia
Cohen‐Mansfield, J., Parpura‐Gill, A., & Golander, H. (2006) · The Journals of Gerontology Series B · doi:10.1093/geronb/61.4.p202 · Cited by 153 · see citing works
Rabinowitz, J., Davidson, M., Deyn, P. P. D., Katz, I., Brodaty, H., & Cohen-Mansfield, J. (2005) · American Journal of Geriatric Psychiatry · doi:10.1176/appi.ajgp.13.11.991 · Cited by 104 · see citing works
Non‐pharmacological management of behavioural symptoms in nursing homes
Deudon, A., Maubourguet, N., Gervais, X., Leone, E., Brocker, P., Carcaillon, L., Riff, S., Lavallart, B., & Robert, P. H. (2009) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.2275 · Cited by 102 · see citing works
Dressing of Cognitively Impaired Nursing Home Residents: Description and Analysis
Cohen‐Mansfield, J., Creedon, M. A., Malone, T., Parpura‐Gill, A., Dakheel‐Ali, M., & Heasly, C. (2006) · The Gerontologist · doi:10.1093/geront/46.1.89 · Cited by 68 · see citing works
Actigraphic measurement of agitated behaviour in dementia
Nagels, G., Engelborghs, S., Vloeberghs, E., Dam, D. V., Pickut, B. A., & Deyn, P. P. D. (2006) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1483 · Cited by 66 · see citing works
The utility and generality of Mini‐Mental State Examination scores in Alzheimer's disease
Giordani, B., Boivin, M. J., Hall, A. L., Foster, N. L., Lehtinen, S., Bluemlein, L. A., & Berent, S. (1990) · Neurology · doi:10.1212/wnl.40.12.1894 · Cited by 60 · see citing works
Estimating the Prevalence of Agitation in Community-Dwelling Persons With Alzheimer's Disease
Tractenberg, R. E., Weiner, M., & Thal, L. J. (2002) · Journal of Neuropsychiatry · doi:10.1176/jnp.14.1.11 · Cited by 50 · see citing works
Temporal Patterns of Agitation in Dementia
Cohen‐Mansfield, J. (2007) · American Journal of Geriatric Psychiatry · doi:10.1097/01.jgp.0000247162.59666.68 · Cited by 39 · see citing works
On-Body Inertial Sensing and Signal Processing for Clinical Assessment of Tremor
Powell, H. C., Jr., Hanson, M. A., & Lach, J. (2009) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2008.2006622 · Cited by 29 · see citing works
Actometry and Barnes Akathisia Rating Scale in neuroleptic-induced akathisia
Janno, S., Holi, M. M., Tuisku, K., & Wahlbeck, K. (2004) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2004.05.003 · Cited by 23 · see citing works
A Wearable Inertial Sensing Technology for Clinical Assessment of Tremor
Powell, H. C., Jr., Hanson, M. A., & Lach, J. (2007) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2007.4463296 · Cited by 23 · see citing works
Teager energy assessment of tremor severity in clinical application of wearable inertial sensors
Hanson, M. A., Powell, H., Frysinger, R. C., Huss, D., Elias, W. J., Lach, J., & Brown, C. L. (2007) · IEEE/NIH Life Science Systems and Applications Workshop · doi:10.1109/lssa.2007.4400903 · Cited by 18 · see citing works
Remote Measurement Methods for User-Centered Design of Telesupport Systems
Smith‐Jackson, T. L., & Williges, R. C. (2001) · Assistive Technology · doi:10.1080/10400435.2001.10132041 · Cited by 7 · see citing works
The Validity of Cognitive Testing in Screening for Dementia
Stockton, P., Cohen‐Mansfield, J., & Billig, N. (1998) · Journal of Medical Systems · doi:10.1023/a:1022602421947 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Vredenburg K, Isensee S, Righi C. User-centered design: an inte- grated approach. Upper Saddle River, NJ: Prentice Hall, PTR; 2002.
Cited by
Sorted by citations
Zucchella, C., Sinforiani, E., Tamburin, S., Federico, A., Mantovani, E., Bernini, S., Casale, R., & Bartolo, M. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.01058 · Cited by 297 · see citing works
“ICT can be used for the assessment of agitation, one of the most challenging symptoms to manage for caregivers (286, 287).”
MethodHusebo, B. S., Heintz, H., Berge, L. I., Owoyemi, P., Rahman, A. T., & Vahia, I. V. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.01699 · Cited by 98 · see citing works
Detecting agitation and aggression in people with dementia using sensors—A systematic review
Khan, S. S., Ye, B., Taati, B., & Mihailidis, A. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.02.004 · Cited by 94 · see citing works
“Eight studies showed some evidence of correlation between actigraphy and agitation in PwDs [1,6,8,10,14,15,18,24].”
BackgroundMethodResultInfluentialIaboni, A., Spasojevic, S. S., Newman, K., Martin, L. S., Wang, A. H., Ye, B., Mihailidis, A., & Khan, S. S. (2022) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12305 · Cited by 71 · see citing works
Teipel, S. J., König, A., Hoey, J., Kaye, J. A., Krüger, F., Robillard, J. M., Kirste, T., & Babiloni, C. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.05.003 · Cited by 66 · see citing works
“[14,44] Wearable sensors to detect agitation and dementia features This study provides an accelerometric motion score related to cognitive decline.”
Tabbaa, L., Ang, C. S., Rose, V., Siriaraya, P., Stewart, I., Jenkins, K. G., & Matsangidou, M. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300466 · Cited by 50 · see citing works
“Such research is mostly aimed at providing interventions for training [4, 5] , assistive technology (see a summary in [6]), detection and assessment [7, 8] , or reminiscence [9, 10, 11].”
A Pilot Study to Detect Agitation in People Living with Dementia Using Multi-Modal Sensors
Spasojevic, S. S., Nogas, J., Iaboni, A., Ye, B., Mihailidis, A., Wang, A., Li, S. J., Martin, L. S., Newman, K., & Khan, S. S. (2021) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-021-00095-7 · Cited by 48 · see citing works
“The following 10 out of 37 features were extracted from ACC signal: mean, minimum, standard deviation, interquartile range, spectral entropy, DC power, and 4 Teager energy features [11, 12].”
BackgroundMethodFleiner, T., Leucht, S., Förstl, H., Zijlstra, W., & Häussermann, P. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160683 · Cited by 43 · see citing works
Bankole, A., Anderson, M. S., Homdee, N., Alam, R., Lofton, A., Fyffe, N., Goins, H., Newbold, T., Smith‐Jackson, T. L., & Lach, J. (2020) · American Journal of Alzheimer s Disease & Other Dementias® · doi:10.1177/1533317520906686 · Cited by 35 · see citing works
Lazarou, I., Stavropoulos, T. G., Μεδίτσκος, Γ., Andreadis, S. T., Kompatsiaris, I. Y., & Tsolaki, M. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-190423 · Cited by 35 · see citing works
“Another study of the same size [55] examined the ability of a custom Body Sensor Network (BSN) to capture the presence of agitation against currently accepted subjective neuropsychological measures and to discriminate between agitation and cognitive decline.”
Göerß, D., Hein, A., Bader, S., Halek, M., Kernebeck, S., Kutschke, A., Heine, C., Krueger, F. W., Kirste, T., & Teipel, S. J. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.08.193 · Cited by 28 · see citing works
Nirjon, S., Greenwood, C., Torres, C., Zhou, S., Stankovic, J. A., Yoon, H. J., Ra, H.-K., Basaran, C., Park, T., & Son, S. H. (2014) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2014.6813937 · Cited by 26 · see citing works
BESI: Reliable and Heterogeneous Sensing and Intervention for In-home Health Applications
Alam, R., Dugan, J., Homdee, N., Gandhi, N., Ghaemmaghami, B., Meda, H., Bankole, A., Anderson, M. S., Gong, J., Smith‐Jackson, T. L., et al. (2017) · IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies · doi:10.1109/chase.2017.73 · Cited by 25 · see citing works
“demonstrated the ability of inertial motion signals to validly assess physical agitation of dementia patients based on their movement data in controlled clinical settings [44].”
BackgroundCheung, J. C., So, B. P.-H., Ho, K. H. M., Wong, D. W., Lam, A. H. F., & Cheung, D. S. K. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.913213 · Cited by 22 · see citing works
“Both Knuff et al. (26) and Nagels et al. (38) divided the participants into those exhibiting high and low levels of agitation at a cut-off point of 50 for the CMAI total score.”
BackgroundMethodInfluentialChikhaoui, B., Ye, B., & Mihailidis, A. (2016) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-016-0415-y · Cited by 23 · see citing works
“In Bankole et al.’s work (Bankole et al. 2012), the authors investigated body sensor network technology in the detection of agitation in older adults with dementia.”
BackgroundAgitation Monitoring and Prevention System for Dementia Caregiver Empowerment
Homdee, N., Alam, R., Hayes, J., Hamid, T., Park, J., Wolfe, S., Goins, H., Fyffe, N., Newbold, T., Smith‐Jackson, T. L., et al. (2019) · Computer · doi:10.1109/mc.2019.2933192 · Cited by 21 · see citing works
Women Coping With a Partner's Dementia‐Related Violence: A Qualitative Study
Band‐Winterstein, T., & Avieli, H. (2019) · Journal of Nursing Scholarship · doi:10.1111/jnu.12485 · Cited by 17 · see citing works
Maximizing ADL Performance to Facilitate Aging in Place for People with Dementia
Ciro, C. A. (2014) · Nursing Clinics of North America · doi:10.1016/j.cnur.2014.02.004 · Cited by 17 · see citing works
Correlates Among Nocturnal Agitation, Sleep, and Urinary Incontinence in Dementia
Rose, K. M., Specht, J. P., & Forch, W. (2014) · American Journal of Alzheimer s Disease & Other Dementias® · doi:10.1177/1533317514524814 · Cited by 17 · see citing works
“A pilot study was conducted with 6 elderly residents with dementia living in long-term care identified as being at high risk of agitated behaviors.(22) Nine hours of data were collected from each resident using devices applied at 3 sites while behaviors were simultaneously observed and annotated.”
BackgroundMethodInfluentialBehavioral Interventions for Alzheimer’s Management Using Technology: Home-Based Monitoring
Anderson, M. S., Homdee, N., Bankole, A., Alam, R., Mitchell, B. A., Hayes, J., Byfield, G. E., & Lach, J. (2020) · Current Geriatrics Reports · doi:10.1007/s13670-020-00312-y · Cited by 14 · see citing works
Fleiner, T., Zijlstra, W., Dauth, H., & Häussermann, P. (2015) · Trials · doi:10.1186/s13063-015-0758-2 · Cited by 14 · see citing works
“The results of our planned trial may help to implement and improve the clinical use of body-fixed sensors in assessing circadian and behavioural symptoms in patients suffering from dementia [46, 53].”
BackgroundBoyle, L. D., Giriteka, L., Marty, B., Steihaug, O. M., Haugarvoll, K., Sandgathe, L., Husebo, B. S., & Pătraşcu, M. (2025) · Sensors · doi:10.3390/s25030668 · Cited by 10 · see citing works
“Most of the management nine included this umbrella We, therefore, studies [34–61 focused on the and sleep the measurement of these less researched digital biomarkers for future studies.”
Xu, J., Smaling, H. J. A., Schoones, J. W., Achterberg, W. P., & van der Steen, J. T. (2024) · BMC Palliative Care · doi:10.1186/s12904-024-01371-0 · Cited by 10 · see citing works
“Among nursing home residents with dementia, actigraphy demonstrated acceptable discriminant validity compared with the Mini-Mental State Examination, which measured a different concept [51].”
ResultRose, K. M., Lach, J., Perkhounkova, Y., Gong, J., Dandu, S. R., Dickerson, R. F., Emi, I. A., Fan, D., Specht, J. P., & Stankovic, J. A. (2018) · Journal of Gerontological Nursing · doi:10.3928/00989134-20180626-03 · Cited by 9 · see citing works
Challenges of collecting empirical sensor data from people with dementia in a field study
Hein, A., Krüger, F., Bader, S., Eschholz, P., & Kirste, T. (2017) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2017.7917512 · Cited by 9 · see citing works
“[1], [2] observed 6 patients with dementia for 3 x 3h using 3 accelerometers at the dominant wrist, waist, and opposite leg.”
MethodWijbenga, R. A., Blaauw, F. J., Janus, S. I. M., Tibben, C., Smits, A. E., Voshaar, R. C. O., Zuidema, S. U., & Zuidersma, M. (2021) · Aging & Mental Health · doi:10.1080/13607863.2021.1935464 · Cited by 7 · see citing works
Assessing BESI mobile application usability for caregivers of persons with dementia
Sourbeer, K., Bankole, A., Anderson, M. S., Newbold, T., Nama, R., Belay, M., Meda, H., & Smith‐Jackson, T. L. (2018) · Gerontechnology · doi:10.4017/gt.2018.17.2.004.00 · Cited by 6 · see citing works
Size of Core Network: Why Less May Be More for Older Adults with Dementia
Ghassani, A. A., & Rababa, M. (2021) · Ageing International · doi:10.1007/s12126-021-09414-0 · Cited by 5 · see citing works
Agitation in people with dementia: A concept analysis
Ghassani, A. A., Rababa, M., & Khait, A. F. A. (2021) · Nursing Forum · doi:10.1111/nuf.12629 · Cited by 4 · see citing works
The Significance and Limitations of Sensor-based Agitation Detection in People Living with Dementia
Sandhu, M. M., Prabhu, D., Lü, W., Kholghi, M., Packer, K., Higgins, L., Varnfield, M., & Silvera‐Tawil, D. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10340349 · Cited by 4 · see citing works
“Furthermore, informant rating methods require significant time from skilled professionals (and may potentially trigger caregiver ‘burnout’), making them ineffective and inefficient [17] for continuous and longitudinal monitoring of PLwD.”
BackgroundNirjon, S., Greenwood, C., Torres, C., Zhou, S., Stankovic, J. A., Yoon, H. J., Ra, H.-K., Basaran, C., Park, T., & Son, S. H. (2013) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/2517351.2517396 · Cited by 4 · see citing works
Li, H., Rezvani, R., Kolanko, M., Sharp, D. J., Wairagkar, M., Vaidyanathan, R., Nilforooshan, R., & Barnaghi, P. M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2101.07007 · Cited by 4 · see citing works
“Much of the previous work focused on detection and prediction of falls using wearable accelerometers or other motion detectors [35], as well as tracking behavioural symptoms such as sleep disturbances [36], agitation [37], and wandering [38] in elderly patients.”
BackgroundA Real-Time Detection of Patient's Aggressive Behaviors on a Smart Sensor
Inoue, Y., & Moshnyaga, V. G. (2024) · IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) · doi:10.1109/mwscas60917.2024.10658928 · Cited by 3 · see citing works
A Data Framework to Understand the Lived Context for Dementia Caregiver Empowerment.
Belay, M., Henry, C. A., Wynn, D., & Smith‐Jackson, T. L. (2015) · MAICS · Cited by 3 · see citing works
Li, H., Kolanko, M., Enshaeifar, S., Skillman, S., Markides, A., Kenny, M., Soreq, E., Kouchaki, S., Jensen, K., Cameron, L. P., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.13916 · Cited by 2 · see citing works
Ciarmoli, D. (2021) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-7998-7430-0.ch009
Prediction of BPSD Using Environmental and Vital Sensor Data
Onuma, H., Tokiwa, N., Shibata, J., Suzuki, T., Kashiwagi, T., Moe, T., Kamura, K., Shinmi, T., Tano, S., & Minami, Y. (2024) · IEEE International Conference on Artificial Intelligence for Medicine, Health and Care (AIMHC) · doi:10.1109/aimhc59811.2024.00017
Turley, K., Rafferty, J., Bond, R., Mulvenna, M. D., Ryan, A. A., & Crawford, L. (2025) · Lighting Research & Technology · doi:10.1177/14771535251315476
- Authors
- Bankole, A., Anderson, M., Smith-Jackson, T., Knight, A., Oh, K., Brantley, J., Barth, A., & Lach, J.
- Affiliations
- Carilion Roanoke Memorial Hospital (US)
- Grado Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
- Virginia Tech (US)
- University of Virginia (US)
- Wireless Health Interactive LLC, Vienna, VA, USA
- Corresponding author
- Bankole, Azziza
- Venue
- American Journal of Alzheimer's Disease & Other Dementias®
- Publisher
- SAGE Publications
- Published
- 2012-07-19
- Volume
- 27
- Issue
- 5
- Pages
- 346-354
- ISSN
- 0888-4897 (ISSN-L)
- 1533-3175
- 1938-2731
- PMC
- PMC10845589
- OpenAlex
- W1991303244
- Cited by
- 40
- References
- 36
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 1 · 2022: 2 · 2021: 6 · 2020: 4 · 2019: 5 · 2018: 5 · 2017: 2 · 2016: 3 · 2015: 2 · 2014: 4 · 2013: 1
- FWCI
- 1.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Alzheimer s Disease & Other Dementias® (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Carilion Clinic
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- wireless body area networks, agitation detection, dementia, non-invasive monitoring, Cohen-Mansfield Agitation Inventory, cognitive decline, long-term care, sensor validation, construct validity
- MeSH terms
- Aged, Aged, 80 and over, Dementia, Female, Humans, Monitoring, Physiologic, Neuropsychological Tests, Pilot Projects, Predictive Value of Tests, Psychomotor Agitation, Sensitivity and Specificity, Reproducibility of Results, Accelerometry
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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