Assessment of Arm Activity Using Triaxial Accelerometry in Patients With a Stroke

van der Pas, Sanne C.; Verbunt, Jeanine A.; Breukelaar, Dorien E.; van Woerden, Rachma; Seelen, Henk A.

doi:10.1016/j.apmr.2011.02.021

Cited by 131Stroke Rehabilitation and RecoveryContext-Aware Activity Recognition SystemsPhysical Activity and Health

Assessment of Arm Activity Using Triaxial Accelerometry in Patients With a Stroke

van der Pas, Sanne C., Verbunt, Jeanine A., Breukelaar, Dorien E., van Woerden, Rachma, Seelen, Henk A.·2011·Archives of Physical Medicine and Rehabilitation

DOI 10.1016/j.apmr.2011.02.021

Open this paper in CoChat — free account

Abstract

Objective To study the validity of accelerometry in the assessment of arm activity of patients with impaired arm function after stroke.Design Cross-sectional concurrent validity study.Setting Rehabilitation center.Participants Patients (N=45) at different stages after stroke.Interventions Not applicable.Main outcome measures All patients wore 2 triaxial accelerometers around their wrists during 3 consecutive days. Arm activity was assessed, based on unilateral (activity of the affected arm) and bilateral accelerometry (ratio between the activity of the affected and nonaffected arm). The Motor Activity Log-26 (MAL-26) Amount of Use (AOU) scale was used as the main external criterion to test the concurrent validity of arm accelerometry. In addition, the MAL-26 Quality of Movement (QOM) scale and the Stroke Impact Scale (SIS) subscale Hand Function were used. To test the divergent validity, the SIS subscale Mobility was used. Spearman correlation coefficients were calculated. In an additional regression analysis, the hypothesized confounding influence of spasm, therapy intensity, and interobserver differences was studied.Results Both unilateral (ρ=.58, P<.001) and bilateral (ρ=.60, P<.001) accelerometry were significantly related to the MAL-AOU scale. Associations of both unilateral and bilateral accelerometry with the MAL-QOM and SIS subscale Hand Function corroborated these findings. The SIS subscale Mobility was not significantly associated with unilateral accelerometry (ρ=.41, P=.01) or bilateral accelerometry (ρ=.23, P=.11). None of the hypothesized confounders influenced these associations significantly.Conclusions Based on the results, both the concurrent and divergent validity of unilateral and bilateral arm accelerometry for measuring arm activity after stroke are good.

Integrity signals

Registry

Crossref · 10.1016/j.apmr.2011.02.021

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

In stroke, upper extremity activity, walking, and physical activity levels were investigated using step and activity counts.
“In stroke, upper extremity activity [40–51], walking, and physical activity levels were investigated in several studies using step and activity counts [52–62].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [46]
Moderate-to-strong correlations were found between accelerometer measures and clinical upper extremity scales in chronic stroke.
“Moderate-to-strong correlations were found between accelerometer measures (threshold-based counts per time unit) and clinical upper extremity scales in chronic stroke [46, 49].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [46]

Probability of Regaining Dexterity in the Flaccid Upper Limb
Kwakkel, G., Kollen, B. J., van der Grond, J., & Prevo, A. J. H. (2003) · Stroke · doi:10.1161/01.str.0000087172.16305.cd · Cited by 1,409 · see citing works
The Stroke Impact Scale Version 2.0
Duncan, P. W., Wallace, D., Lai, S. M., Johnson, D. E., Embretson, S. E., & Laster, L. J. (1999) · Stroke · doi:10.1161/01.str.30.10.2131 · Cited by 1,180 · see citing works
On the Validity of the Beck Depression Inventory
Richter, P., Werner, J., Heerlein, A., Kraus, A., & Sauer, H. (1998) · Psychopathology · doi:10.1159/000066239 · Cited by 1,113 · see citing works
Rasch analysis of a new stroke-specific outcome scale: the stroke impact scale11No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the author(s) or upon any organization with which the author(s) is/are associated.
Duncan, P. W., Bode, R. K., Lai, S. M., & Perera, S. (2003) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/s0003-9993(03)00035-2 · Cited by 913 · see citing works
Accelerometer Use in Physical Activity: Best Practices and Research Recommendations
WARD, D. S., EVENSON, K. R., VAUGHN, A., RODGERS, A. B., & TROIANO, R. P. (2005) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000185292.71933.91 · Cited by 779 · see citing works
The hemiplegic arm after stroke: measurement and recovery.
Wade, D. T., Langton-Hewer, R., WOOD, V. A., Skilbeck, C. E., & Ismail, H. M. (1983) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.46.6.521 · Cited by 620 · see citing works
Validity of the Beck Depression Inventory, Hospital Anxiety and Depression Scale, SCL-90, and Hamilton Depression Rating Scale as Screening Instruments for Depression in Stroke Patients
Aben, I., Verhey, F. R. J., Lousberg, R. L., Lodder, J., & Honig, A. (2002) · Psychosomatics · doi:10.1176/appi.psy.43.5.386 · Cited by 573 · see citing works
Reliability and Validity of the Upper-Extremity Motor Activity Log-14 for Measuring Real-World Arm Use
Uswatte, G., Taub, E., Morris, D. M., Vignolo, M. J., & McCulloch, K. L. (2005) · Stroke · doi:10.1161/01.str.0000185928.90848.2e · Cited by 519 · see citing works
The learned nonuse phenomenon: implications for rehabilitation.
Taub, E., Uswatte, G., Mark, V. W., & Morris, D. M. (2006) · PubMed · Cited by 517 · see citing works
Assessment of physical activity: a critical appraisal
Westerterp, K. R. (2009) · European Journal of Applied Physiology · doi:10.1007/s00421-009-1000-2 · Cited by 460 · see citing works
The Motor Activity Log-28
Uswatte, G., Taub, E., Morris, D. M., Light, K. E., & Thompson, P. A. (2006) · Neurology · doi:10.1212/01.wnl.0000238164.90657.c2 · Cited by 459 · see citing works
Clinimetric Properties of the Motor Activity Log for the Assessment of Arm Use in Hemiparetic Patients
van der Lee, J. H., Beckerman, H., Knol, D. L., de Vet, H. C. W., & Bouter, L. M. (2004) · Stroke · doi:10.1161/01.str.0000126900.24964.7e · Cited by 451 · see citing works
Mechanisms underlying recovery of motor function after stroke
Ward, N. (2005) · Postgraduate medical journal · doi:10.1136/pgmj.2004.030809 · Cited by 324 · see citing works
Monitoring of Physical Activity after Stroke: A Systematic Review of Accelerometry-Based Measures
Gebruers, N., Vanroy, C., Truijen, S., Engelborghs, S., & De Deyn, P. P. (2010) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2009.10.025 · Cited by 293 · see citing works
Arm and leg paresis as outcome predictors in stroke rehabilitation.
Olsen, T. S. (1990) · Stroke · doi:10.1161/01.str.21.2.247 · Cited by 292 · see citing works
Validity of Accelerometry for Monitoring Real-World Arm Activity in Patients With Subacute Stroke: Evidence From the Extremity Constraint-Induced Therapy Evaluation Trial
Uswatte, G., Giuliani, C., Winstein, C., Zeringue, A., Hobbs, L., & Wolf, S. L. (2006) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2006.06.006 · Cited by 241 · see citing works
Ambulatory Monitoring of Arm Movement Using Accelerometry: An Objective Measure of Upper-Extremity Rehabilitation in Persons With Chronic Stroke
Uswatte, G., Foo, W. L., Olmstead, H., Lopez, K., Holand, A., & Simms, L. B. (2005) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2005.01.010 · Cited by 233 · see citing works
Objective Measurement of Functional Upper-Extremity Movement Using Accelerometer Recordings Transformed With a Threshold Filter
Uswatte, G., Miltner, W. H. R., Foo, B., Varma, M., Moran, S., & Taub, E. (2000) · Stroke · doi:10.1161/01.str.31.3.662 · Cited by 233 · see citing works
Upper Extremity Use in People with Hemiparesis in the First Few Weeks After Stroke
Lang, C. E., Wagner, J. M., Edwards, D. F., & Dromerick, A. W. (2007) · Journal of Neurologic Physical Therapy · doi:10.1097/npt.0b013e31806748bd · Cited by 216 · see citing works
Physical and Social Functioning After Stroke
Lai, S., Perera, S., Duncan, P. W., & Bode, R. K. (2003) · Stroke · doi:10.1161/01.str.0000054162.94998.c0 · Cited by 158 · see citing works
Measuring Free-Living Physical Activity in Adults With and Without Neurologic Dysfunction With a Triaxial Accelerometer
Hale, L. A., Pal, J., & Becker, I. (2008) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2008.02.027 · Cited by 118 · see citing works
The Stroke Upper-Limb Activity Monitor: Its Sensitivity to Measure Hemiplegic Upper-Limb Activity During Daily Life
de Niet, M., Bussmann, J. B., Ribbers, G. M., & Stam, H. J. (2007) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2007.06.005 · Cited by 94 · see citing works
The validity of questionnaire measures for assessing depression after stroke
Lincoln, N., Nicholl, C., Flannaghan, T., Leonard, M., & der Gucht, E. V. (2003) · Clinical Rehabilitation · doi:10.1191/0269215503cr687oa · Cited by 88 · see citing works
Ambulatory measurement of upper limb usage and mobility-related activities during normal daily life with an upper limb-activity monitor: A feasibility study
Schasfoort, F. C., Bussmann, J. B. J., & Stam, H. J. (2002) · Medical & Biological Engineering & Computing · doi:10.1007/bf02348122 · Cited by 50 · see citing works
Impact of upper limb complex regional pain syndrome type 1 on everyday life measured with a novel upper limb-activity monitor
Schasfoort, F. C., Bussmann, J. B. J., Zandbergen, A. M. A. J., & Stam, H. J. (2002) · Pain · doi:10.1016/s0304-3959(02)00298-1 · Cited by 48 · see citing works

Flagged first, then by citations

1 of the 26 references couldn’t be matched to a known paper.

Sorted by citations

Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making
Lang, C. E., Bland, M. D., Bailey, R. R., Schaefer, S. Y., & Birkenmeier, R. L. (2012) · Journal of Hand Therapy · doi:10.1016/j.jht.2012.06.005 · Cited by 388 · see citing works
Quantifying Real-World Upper-Limb Activity in Nondisabled Adults and Adults With Chronic Stroke
Bailey, R. R., Klaesner, J. W., & Lang, C. E. (2015) · Neurorehabilitation and neural repair · doi:10.1177/1545968315583720 · Cited by 263 · see citing works
Arm Motor Recovery Using a Virtual Reality Intervention in Chronic Stroke
Subramanian, S. K., Lourenço, C. B., Chilingaryan, G., Sveistrup, H., & Levin, M. F. (2012) · Neurorehabilitation and neural repair · doi:10.1177/1545968312449695 · Cited by 219 · see citing works
Association of Irisin with Fat Mass, Resting Energy Expenditure, and Daily Activity in Conditions of Extreme Body Mass Index
Pardo, M., Crujeiras, A. B., Amil, M., Agüera, Z., Jiménez‐Múrcia, S., Baños, R., Botella, C., de la Torre, R., Estivill, X., Fagundo, A. B., et al. (2014) · International Journal of Endocrinology · doi:10.1155/2014/857270 · Cited by 216 · see citing works
Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review.
Block, V. A. J., Pitsch, E., Tahir, P., Cree, B. A. C., Allen, D. D., & Gelfand, J. M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0154335 · Cited by 198 · see citing works
“Cancela et al, 2014 [125] Mild PERFORM (a*) Walking /gait/ LE physical activity Crosssectional > 50 11 N/A 2–6 days Government/ Private foundation”
BackgroundInfluential
Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review
Johansson, D., Malmgren, K., & Alt Murphy, M. (2018) · Journal of Neurology · doi:10.1007/s00415-018-8786-y · Cited by 188 · see citing works
Computational neurorehabilitation: modeling plasticity and learning to predict recovery
Reinkensmeyer, D. J., Burdet, E., Casadio, M., Krakauer, J. W., Kwakkel, G., Lang, C. E., Swinnen, S. P., Ward, N., & Schweighofer, N. (2016) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-016-0148-3 · Cited by 181 · see citing works
Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits
Newbold, D. J., Laumann, T. O., Hoyt, C. R., Hampton, J. M., Montez, D. F., Raut, R. V., Ortega, M., Mitra, A., Nielsen, A. N., Miller, D. B., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.05.007 · Cited by 174 · see citing works
Competitive and cooperative arm rehabilitation games played by a patient and unimpaired person: effects on motivation and exercise intensity
Goršič, M., Cikajlo, I., & Novak, D. (2017) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-017-0231-4 · Cited by 150 · see citing works
An Accelerometry-Based Methodology for Assessment of Real-World Bilateral Upper Extremity Activity
Bailey, R. R., Klaesner, J. W., & Lang, C. E. (2014) · PLoS ONE · doi:10.1371/journal.pone.0103135 · Cited by 149 · see citing works
Accelerometer measurement of upper extremity movement after stroke: a systematic review of clinical studies
Noorkõiv, M., Rodgers, H., & Price, C. I. (2014) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-11-144 · Cited by 141 · see citing works
A remote quantitative fugl-meyer assessment framework for stroke patients based on wearable sensor networks
Yu, L., Xiong, D., Guo, L., & Wang, J. (2016) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2016.02.012 · Cited by 134 · see citing works
Exploring the Role of Accelerometers in the Measurement of Real World Upper-Limb Use After Stroke
Hayward, K. S., Eng, J. J., Boyd, L. A., Lakhani, B., Bernhardt, J. A., & Lang, C. E. (2015) · Brain Impairment · doi:10.1017/brimp.2015.21 · Cited by 126 · see citing works
Enabling stroke rehabilitation in home and community settings: a wearable sensor-based approach for upper-limb motor training
Lee, S. I., Adans-Dester, C. P., Grimaldi, M., Dowling, A. V., Horak, P. C., Black-Schaffer, R. M., Bonato, P., & Gwin, J. T. (2018) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2018.2829208 · Cited by 119 · see citing works
Upper-limb activity in adults: Referent values using accelerometry
Bailey, R. R., MSOT, Lang, C. E., & PT (2013) · The Journal of Rehabilitation Research and Development · doi:10.1682/jrrd.2012.12.0222 · Cited by 114 · see citing works
Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field
Lang, C. E., Barth, J., Holleran, C. L., Konrad, J. D., & Bland, M. D. (2020) · Sensors · doi:10.3390/s20205744 · Cited by 105 · see citing works
The Manumeter: A Wearable Device for Monitoring Daily Use of the Wrist and Fingers
Friedman, N., Rowe, J. B., Reinkensmeyer, D. J., & Bachman, M. (2014) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2329841 · Cited by 99 · see citing works
A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
Lang, C. E., Waddell, K. J., Klaesner, J. W., & Bland, M. D. (2017) · Journal of Visualized Experiments · doi:10.3791/55673 · Cited by 96 · see citing works
A method to qualitatively assess arm use in stroke survivors in the home environment
Leuenberger, K., Gonzenbach, R. R., Wachter, S., Luft, A. R., & Gassert, R. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-016-1496-7 · Cited by 86 · see citing works
Improvement in the Capacity for Activity Versus Improvement in Performance of Activity in Daily Life During Outpatient Rehabilitation
Lang, C. E., Holleran, C. L., Strube, M., Ellis, T. D., Newman, C. A., Fahey, M., DeAngelis, T. R., Nordahl, T. J., Reisman, D. S., Earhart, G. M., et al. (2022) · Neurology Report · doi:10.1097/npt.0000000000000413 · Cited by 81 · see citing works
A multisession evaluation of an adaptive competitive arm rehabilitation game
Goršič, M., Cikajlo, I., Goljar, N., & Novak, D. (2017) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-017-0336-9 · Cited by 79 · see citing works
Trends in robot-assisted and virtual reality-assisted neuromuscular therapy: a systematic review of health-related multiplayer games
Baur, K., Schättin, A., de Bruin, E. D., Riener, R., Duarte, J. E., & Wolf, P. (2018) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0449-9 · Cited by 72 · see citing works
Validity of Body-Worn Sensor Acceleration Metrics to Index Upper Extremity Function in Hemiparetic Stroke
Urbin, M. A., Bailey, R. R., & Lang, C. E. (2015) · Neurology Report · doi:10.1097/npt.0000000000000085 · Cited by 69 · see citing works
Inertial Sensor Measurements of Upper-Limb Kinematics in Stroke Patients in Clinic and Home Environment
Held, J. P. O., Klaassen, B., Eenhoorn, A., van Beijnum, B.-J. F., Buurke, J. H., Veltink, P. H., & Luft, A. R. (2018) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2018.00027 · Cited by 69 · see citing works
Effect of Mental Practice on the Improvement of Function and Daily Activity Performance of the Upper Extremity in Patients With Subacute Stroke: A Randomized Clinical Trial
Timmermans, A. A. A., Verbunt, J., van Woerden, R., Moennekens, M., Pernot, D., & Seelen, H. A. M. (2012) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2012.10.010 · Cited by 68 · see citing works
Self-citation
Perceived and actual arm performance in multiple sclerosis: relationship with clinical tests according to hand dominance
Lamers, I., Kerkhofs, L., Raats, J., Kos, D., Wijmeersch, B. V., & Feys, P. (2013) · Multiple Sclerosis Journal · doi:10.1177/1352458513475832 · Cited by 62 · see citing works
Real-world affected upper limb activity in chronic stroke: an examination of potential modifying factors
Bailey, R. R., Birkenmeier, R. L., & Lang, C. E. (2015) · Topics in Stroke Rehabilitation · doi:10.1179/1074935714z.0000000040 · Cited by 58 · see citing works
Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method
Lum, P. S., Shu, L., Bochniewicz, E. M., Tran, T., Chang, L., Barth, J., & Dromerick, A. W. (2020) · Neurorehabilitation and neural repair · doi:10.1177/1545968320962483 · Cited by 60 · see citing works
Accelerometer-Based Monitoring of Upper Limb Movement in Older Adults With Acute and Subacute Stroke
Narai, E., Hagino, H., Komatsu, T., & Togo, F. (2015) · Journal of Geriatric Physical Therapy · doi:10.1519/jpt.0000000000000067 · Cited by 57 · see citing works
A low cost kinect-based virtual rehabilitation system for inpatient rehabilitation of the upper limb in patients with subacute stroke
Kim, W., Cho, S. M., Park, S. H., Lee, J.-Y., Kwon, S., & Paik, N. (2018) · Medicine · doi:10.1097/md.0000000000011173 · Cited by 57 · see citing works
Comparison of Kinect2Scratch game-based training and therapist-based training for the improvement of upper extremity functions of patients with chronic stroke: a randomized controlled single-blinded trial
Hung, J.-W., Chou, C., Chang, Y., Wu, C., Chang, K., Wu, W., & Howell, S. (2019) · European Journal of Physical and Rehabilitation Medicine · doi:10.23736/s1973-9087.19.05598-9 · Cited by 55 · see citing works
Accelerometry Measuring the Outcome of Robot-Supported Upper Limb Training in Chronic Stroke: A Randomized Controlled Trial
Lemmens, R. J. M., Timmermans, A. A. A., Janssen‐Potten, Y., Pulles, A. N. T. D., Geers, R. P. J., Bakx, W. G. M., Smeets, R., & Seelen, H. A. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096414 · Cited by 53 · see citing works
Self-citation
Moderate-Vigorous Physical Activity across Body Mass Index in Females: Moderating Effect of Endocannabinoids and Temperament
Fernández‐Aranda, F., Sauchelli, S., Pastor, A., González, M. L., de la Torre, R., Granero, R., Jiménez‐Múrcia, S., Baños, R., Botella, C., Fernández‐Real, J. M., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104534 · Cited by 50 · see citing works
Rating of Everyday Arm-Use in the Community and Home (REACH) Scale for Capturing Affected Arm-Use after Stroke: Development, Reliability, and Validity
Simpson, L. A., Eng, J. J., Backman, C. L., & Miller, W. C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083405 · Cited by 45 · see citing works
A novel upper-limb function measure derived from finger-worn sensor data collected in a free-living setting
Lee, S. I., Liu, X., Rajan, S., Ramasarma, N., Choe, E. K., & Bonato, P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0212484 · Cited by 43 · see citing works
A new way of assessing arm function in activity using kinematic Exposure Variation Analysis and portable inertial sensors—A validity study
Ertzgaard, P., Öhberg, F., Gerdle, B., & Grip, H. (2016) · Manual Therapy · doi:10.1016/j.math.2015.09.004 · Cited by 41 · see citing works
Changes in actual arm-hand use in stroke patients during and after clinical rehabilitation involving a well-defined arm-hand rehabilitation program: A prospective cohort study
Franck, J. A., Smeets, R., & Seelen, H. A. M. (2019) · PLoS ONE · doi:10.1371/journal.pone.0214651 · Cited by 41 · see citing works
Self-citation
Characterizing upper extremity motor behavior in the first week after stroke
Barth, J., Geed, S., Mitchell, A., Lum, P. S., Edwards, D. F., & Dromerick, A. W. (2020) · PLoS ONE · doi:10.1371/journal.pone.0221668 · Cited by 41 · see citing works
A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
Lang, C. E., Waddell, K. J., Klaesner, J. W., & Bland, M. D. (2017) · Journal of Visualized Experiments · doi:10.3791/55673-v · Cited by 41 · see citing works
The use of a finger-worn accelerometer for monitoring of hand use in ambulatory settings
Liu, X., Rajan, S., Ramasarma, N., Bonato, P., & Lee, S. I. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2018.2821136 · Cited by 39 · see citing works
Monitoring motor capacity changes of children during rehabilitation using body-worn sensors
Strohrmann, C., Labruyère, R., Gerber, C. N., van Hedel, H. J. A., Bert Arnrich, A., & Tröster, G. (2013) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-10-83 · Cited by 40 · see citing works
Magnetically Counting Hand Movements: Validation of a Calibration-Free Algorithm and Application to Testing the Threshold Hypothesis of Real-World Hand Use after Stroke
de Lucena, D. S., Rowe, J. B., Chan, V., & Reinkensmeyer, D. J. (2021) · Sensors · doi:10.3390/s21041502 · Cited by 40 · see citing works
Design and pilot evaluation of competitive and cooperative exercise games for arm rehabilitation at home
Goršič, M., & Novak, D. (2016) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2016.7591774 · Cited by 36 · see citing works
Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements
McLeod, A., Bochniewicz, E. M., Lum, P. S., Holley, R. J., Emmer, G., & Dromerick, A. W. (2015) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2015.08.435 · Cited by 37 · see citing works
Comparison of two difficulty adaptation strategies for competitive arm rehabilitation exercises
Goršič, M., Darzi, A., & Novak, D. (2017) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2017.8009320 · Cited by 36 · see citing works
Breaking presence in Immersive Virtual Reality toward behavioral and emotional engagement
Caldas, O. I., Mauledoux, M., Avilés, O., & Rodriguez-Guerrero, C. (2024) · Comput. Methods Programs Biomed. · doi:10.1016/j.cmpb.2024.108124 · Cited by 28 · see citing works
A Survey of Wearable Sensors and Machine Learning Algorithms for Automated Stroke Rehabilitation
Sengupta, N., Rao, A. S., Yan, B., & Palaniswami, M. S. (2024) · IEEE Access · doi:10.1109/access.2024.3373910 · Cited by 36 · see citing works
Wearable sensing for rehabilitation after stroke: Bimanual jerk asymmetry encodes unique information about the variability of upper extremity recovery
de Lucena, D. S., Stoller, O., Rowe, J. B., Chan, V., & Reinkensmeyer, D. J. (2017) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2017.8009477 · Cited by 35 · see citing works
Digital Phenotyping in Clinical Neurology
Gupta, A. S. (2022) · Seminars in Neurology · doi:10.1055/s-0041-1741495 · Cited by 32 · see citing works
Detection of Pediatric Upper Extremity Motor Activity and Deficits With Accelerometry
Hoyt, C. R., Van, A. N., Ortega, M., Koller, J. M., Everett, E. A., Nguyen, A. L., Lang, C. E., Schlaggar, B. L., & Dosenbach, N. U. F. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.2970 · Cited by 32 · see citing works
Towards the Design of a Ring Sensor-based mHealth System to Achieve Optimal Motor Function in Stroke Survivors
Kim, Y., Jung, H.-T., Park, J., Kim, Y., Ramasarma, N., Bonato, P., Choe, E. K., & Lee, S. I. (2019) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3369817 · Cited by 32 · see citing works
Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review
de Quirós, M. B., Douma, E. H., van den Akker‐Scheek, I., Lamoth, C. J. C., & Maurits, N. M. (2022) · Sensors · doi:10.3390/s22031050 · Cited by 32 · see citing works
Visualisation of upper limb activity using spirals
Chadwell, A., Kenney, L. P. J., Granat, M. H., Thies, S. B., Head, J. S., & Galpin, A. J. (2017) · Prosthetics and Orthotics International · doi:10.1177/0309364617706751 · Cited by 32 · see citing works
An investigation of cortical neuroplasticity following stroke in adults: is there evidence for a critical window for rehabilitation?
McDonnell, M. N., Koblar, S. A., Ward, N., Rothwell, J. C., Hordacre, B. G., & Ridding, M. C. (2015) · BMC Neurology · doi:10.1186/s12883-015-0356-7 · Cited by 31 · see citing works
Upper limb use differs among people with varied upper limb impairment levels early post-stroke: a single-site, cross-sectional, observational study
Chin, L. F., Hayward, K. S., & Brauer, S. (2019) · Topics in Stroke Rehabilitation · doi:10.1080/10749357.2019.1690796 · Cited by 29 · see citing works
Everyday movement and use of the arms: Relationship in children with hemiparesis differs from adults
Sokal, B., Uswatte, G., Vogtle, L. K., Byrom, E., & Barman, J. (2015) · Journal of Pediatric Rehabilitation Medicine · doi:10.3233/prm-150334 · Cited by 28 · see citing works
The volume and timing of upper limb movement in acute stroke rehabilitation: still room for improvement
McLaren, R., Signal, N., Lord, S., Taylor, S., Henderson, J., & Taylor, D. (2019) · Disability and Rehabilitation · doi:10.1080/09638288.2019.1590471 · Cited by 26 · see citing works
Objective Assessment of Postoperative Morbidity After Breast Cancer Treatments with Wearable Activity Monitors: The “BRACELET” Study
Bakri, N. A. C., Kwasnicki, R. M., Dhillon, K., Khan, N., Ghandour, O., Cairns, A., Darzi, A. W., & Leff, D. R. (2021) · Annals of Surgical Oncology · doi:10.1245/s10434-021-10458-4 · Cited by 27 · see citing works
Effects of Modified Constraint-Induced Movement Therapy in Real-World Arm Use in Young Children with Unilateral Cerebral Palsy: A Single-Blind Randomized Trial
Hwang, Y., & Kwon, J. (2020) · Neuropediatrics · doi:10.1055/s-0040-1702220 · Cited by 26 · see citing works
Classification of functional and non-functional arm use by inertial measurement units in individuals with upper limb impairment after stroke
Pohl, J., Ryser, A., Veerbeek, J. M., Verheyden, G., Vogt, J. E., Luft, A. R., & Easthope, C. A. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2022.952757 · Cited by 26 · see citing works
The Manumeter: A non-obtrusive wearable device for monitoring spontaneous use of the wrist and fingers
Rowe, J. B., Friedman, N., Bachman, M., & Reinkensmeyer, D. J. (2013) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2013.6650397 · Cited by 26 · see citing works
Remote monitoring of stroke patients' rehabilitation using wearable accelerometers
Halloran, S., Tang, L., Guan, Y., Shi, J. Q., & Eyre, J. A. (2019) · International Symposium on Wearable Computers · doi:10.1145/3341163.3347731 · Cited by 25 · see citing works
Accelerometer Measurements Indicate That Arm Movements of Children With Cerebral Palsy Do Not Increase After Constraint-Induced Movement Therapy (CIMT)
Goodwin, B. M., Sabelhaus, E. K., Pan, Y.-C., Bjornson, K. F., Pham, K. L. D., Walker, W. O., & Steele, K. M. (2020) · American Journal of Occupational Therapy · doi:10.5014/ajot.2020.040246 · Cited by 24 · see citing works
The variable relationship between arm and hand use: A rationale for using finger magnetometry to complement wrist accelerometry when measuring daily use of the upper extremity
Rowe, J. B., Friedman, N., Chan, V., Cramer, S. C., Bachman, M., & Reinkensmeyer, D. J. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6944522 · Cited by 24 · see citing works
mHealth technologies used to capture walking and arm use behavior in adult stroke survivors: a scoping review beyond measurement properties
Torriani‐Pasin, C., Demers, M., Polese, J. C., Bishop, L., Wade, E., Hempel, S., & Winstein, C. J. (2021) · Disability and Rehabilitation · doi:10.1080/09638288.2021.1953623 · Cited by 21 · see citing works
Detection of Unilateral Arm Paresis after Stroke by Wearable Accelerometers and Machine Learning
Wassélius, J., Finn, E. L., Persson, E., Ericson, P., Brogårdh, C. B., Lindgren, A. G., Ullberg, T., & Åström, K. (2021) · Sensors · doi:10.3390/s21237784 · Cited by 23 · see citing works
Novel Sensor Technology To Assess Independence and Limb-Use Laterality in Cervical Spinal Cord Injury
Brogioli, M., Popp, W., Albisser, U., Brust, A. K., Frotzler, A., Gassert, R., Curt, A. E. P., & Starkey, M. L. (2016) · Journal of Neurotrauma · doi:10.1089/neu.2015.4362 · Cited by 22 · see citing works
Reliability of Wearable-Sensor-Derived Measures of Physical Activity in Wheelchair-Dependent Spinal Cord Injured Patients
Schneider, S., Popp, W., Brogioli, M., Albisser, U., Demkó, L., Debecker, I., Velstra, I., Gassert, R., & Curt, A. E. P. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.01039 · Cited by 23 · see citing works
Music meets robotics: a prospective randomized study on motivation during robot aided therapy
Baur, K., Speth, F., Nagle, A., Riener, R., & Klamroth-Marganska, V. (2018) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-018-0413-8 · Cited by 21 · see citing works
Patients’ physiological reactions to competitive rehabilitation therapies assisted by robotic devices
Catalan, J. M., Blanco, A., García-Pérez, J. V., Vales, Y., Martínez-Pascual, D., Ezquerro, S., Garrote, A., Costa, T., Lledó, L. D., & García-Aracil, N. (2023) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-023-01163-2 · Cited by 20 · see citing works
Effects of Different Opponent Types on Motivation and Exercise Intensity in a Competitive Arm Exercise Game
Goršič, M., Hlucny, S. D., & Novak, D. (2019) · Games for Health Journal · doi:10.1089/g4h.2019.0028 · Cited by 20 · see citing works
Position Sense of the Hemiparetic and Non-Hemiparetic Ankle after Stroke: Is the Non-Hemiparetic Ankle also Affected?
Yalçın, E., Akyüz, M., Önder, B., Kurtaran, A., Şen, S. B., & Demır, S. Ö. (2012) · European Neurology · doi:10.1159/000342025 · Cited by 19 · see citing works
Using accelerometry for measurement of motor behavior in children: Relationship of real-world movement to standardized evaluation
Hoyt, C. R., Brown, S., Sherman, S. K., Wood-Smith, M., Van, A. N., Ortega, M., Nguyen, A. L., Lang, C. E., Schlaggar, B. L., & Dosenbach, N. U. F. (2019) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2019.103546 · Cited by 20 · see citing works
Daily Life Activity Routine Discovery in Hemiparetic Rehabilitation Patients Using Topic Models
Derungs, A., Schuster‐Amft, C., Amft, O., Tröster, G., & Seiter, J. (2015) · Methods of Information in Medicine · doi:10.3414/me14-01-0082 · Cited by 18 · see citing works
Robotic and Wearable Sensor Technologies for Measurements/Clinical Assessments
Lambercy, O., Maggioni, S., Lünenburger, L., Gassert, R., & Bolliger, M. (2016) · Springer eBooks · doi:10.1007/978-3-319-28603-7_10 · Cited by 18 · see citing works
Portable Sensors Add Reliable Kinematic Measures to the Assessment of Upper Extremity Function
Öhberg, F., Bäcklund, T., Sundström, N., & Grip, H. (2019) · Sensors · doi:10.3390/s19051241 · Cited by 18 · see citing works
Wearable-Based Kinematic Analysis of Upper-Limb Movements During Daily Activities Could Provide Insights into Stroke Survivors’ Motor Ability
Lee, S. I., Liu, Y., Vergara-Diaz, G. P., Pugliese, B. L., Black‐Schaffer, R. M., Stoykov, M. E., & Bonato, P. (2024) · Neurorehabilitation and neural repair · doi:10.1177/15459683241270066 · Cited by 16 · see citing works
Suitability of accelerometry as an objective measure for upper extremity use in stroke patients
Heye, A.-L., Kersting, C., Kneer, M., & Barzel, A. (2022) · BMC Neurology · doi:10.1186/s12883-022-02743-w · Cited by 15 · see citing works
Differences in Physiological Reactions Due to a Competitive Rehabilitation Game Modality
Catalan, J. M., García-Pérez, J. V., Blanco, A., Martínez-Pascual, D., Lledó, L. D., & García-Aracil, N. (2021) · Sensors · doi:10.3390/s21113681 · Cited by 15 · see citing works
Assessment of Accelerometers for Measuring Upper-Extremity Physical Activity
Lawinger, E., Uhl, T. L., Abel, M. G., & Kamineni, S. (2015) · Journal of Sport Rehabilitation · doi:10.1123/jsr.2013-0140 · Cited by 15 · see citing works
Use of Accelerometry for Long Term Monitoring of Stroke Patients
Lucas, A., Hermiz, J., Labuzetta, J., Arabadzhi, Y., Karanjia, N., & Gilja, V. (2019) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2019.2897306 · Cited by 26 · see citing works
Classifying physical activity research following stroke using the behavioral epidemiologic framework
Cleveland, S., Driver, S. J., Swank, C., & Macklin, S. (2015) · Topics in Stroke Rehabilitation · doi:10.1179/1074935714z.0000000043 · Cited by 14 · see citing works
An exploration into the cortical reorganisation of the healthy hand inupper-limb complex regional pain syndrome
Pietro, F. D., Stanton, T. R., Moseley, G. L., Lotze, M., & McAuley, J. H. (2016) · Scandinavian Journal of Pain · doi:10.1016/j.sjpain.2016.06.004 · Cited by 14 · see citing works
Envisioning the use of in-situ arm movement data in stroke rehabilitation: Stroke survivors’ and occupational therapists’ perspectives
Jung, H.-T., Kim, Y., Lee, J., Lee, S. I., & Choe, E. K. (2022) · PLoS ONE · doi:10.1371/journal.pone.0274142 · Cited by 14 · see citing works
Relationship Between Body-Specific Attention to a Paretic Limb and Real-World Arm Use in Stroke Patients: A Longitudinal Study
Otaki, R., Oouchida, Y., Aizu, N., Sudo, T., Hiroshi, S., Saito, Y., Takemura, S., & Izumi, S. (2022) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.806257 · Cited by 13 · see citing works
Accelerometer assessed upper limb activity in people with stroke: a validation study considering ambulatory and non-ambulatory activities
Bezuidenhout, L., Joseph, C., Einarsson, U., Thurston, C., Hagströmer, M., & Conradsson, D. M. (2021) · Disability and Rehabilitation · doi:10.1080/09638288.2021.2012838 · Cited by 13 · see citing works
A Wearable Bracelet Device for Promoting Arm Use in Stroke Patients
Ballester, B. R., Lathe, A., Duarte, E., Duff, A., & Verschure, P. F. M. J. (2015) · International Congress on Neurotechnology, Electronics and Informatics · doi:10.5220/0005662300240031 · Cited by 13 · see citing works
Measuring Upper Extremity Activity of Children With Unilateral Cerebral Palsy Using Wrist-Worn Accelerometers: A Pilot Study
Srinivasan, S. M., Amonkar, N., Kumavor, P. D., & Bubela, D. J. (2024) · American Journal of Occupational Therapy · doi:10.5014/ajot.2024.050443 · Cited by 11 · see citing works
Factors associated with upper extremity use after stroke: a scoping review of accelerometry studies
Gagné-Pelletier, L., Poitras, I., Roig, M., & Mercier, C. (2025) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-025-01568-1 · Cited by 12 · see citing works
Sensitivity of the accelerometer as a measurement tool for upper extremity movement by stroke patients: a comparison with the action research arm test
Lee, J., Park, J., & Kim, Y.-J. (2015) · Journal of Physical Therapy Science · doi:10.1589/jpts.27.1053 · Cited by 11 · see citing works
Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living
Šlajpah, S., Čebašek, E., Munih, M., & Mihelj, M. (2023) · Sensors · doi:10.3390/s23031289 · Cited by 11 · see citing works
Utility of a unilateral accelerometer for monitoring upper extremity use in subacute stroke patients after discharge from hospital
Wei, X. X., Fong, K. N. K., Chung, R. C. K., Myint, J., Cheung, H. K. Y., & Chow, E. S. L. (2017) · Assistive Technology · doi:10.1080/10400435.2017.1414085 · Cited by 11 · see citing works
A Multisession Evaluation of a Collaborative Virtual Environment for Arm Rehabilitation
Goršič, M., Cikajlo, I., Goljar, N., & Novak, D. (2018) · PRESENCE Virtual and Augmented Reality · doi:10.1162/pres_a_00331 · Cited by 11 · see citing works
Variability Analysis of Therapeutic Movements using Wearable Inertial Sensors
López-Nava, I. H., Bert Arnrich, A., Muñoz-Meléndez, A., & Özgür, A. G. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0645-8 · Cited by 11 · see citing works
Quantifying real‐world upper limb activity via patient‐initiated spontaneous movement in neonatal brachial plexus palsy
Gatward, M. E., Cook, R. N. L., Yang, L. J. ‐., & Brown, S. H. (2022) · PM&R · doi:10.1002/pmrj.12780 · Cited by 10 · see citing works
Finger-Worn Sensors for Accurate Functional Assessment of the Upper Limbs in Real-World Settings
Liu, X., Rajan, S., Ramasarma, N., Bonato, P., & Lee, S. I. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513134 · Cited by 9 · see citing works
Pilot Long-term Evaluation of Competitive and Cooperative Exercise Games in Inpatient Stroke Rehabilitation
Goršič, M., Cikajlo, I., Javh, M., Goljar, N., & Novak, D. (2019) · International Conference on Rehabilitation Robotics · doi:10.1109/icorr.2019.8779514 · Cited by 9 · see citing works
Effects of a Wearable-Based Intervention on the Hemiparetic Upper Limb in Persons With Stroke: A Randomized Controlled Trial
Toh, S. F. M., Lam, W. W. T., González, P. C., & Fong, K. N. K. (2024) · Neurorehabilitation and neural repair · doi:10.1177/15459683241283412 · Cited by 8 · see citing works
Behavioral and Psychophysiological Measures of Engagement During Dynamic Diﬃculty Adjustment in Immersive Virtual Reality
Caldas, O. I., Mauledoux, M., Sánchez, O. F. A., & Rodriguez‐Guerrero, C. (2023) · JUCS - Journal of Universal Computer Science · doi:10.3897/jucs.89412 · Cited by 8 · see citing works
Competitive Versus Cooperative Forms of Therapeutic Gaming With Subacute Stroke Patients
Baur, K., Wolf, P., Novak, D., Boering, D., Hörner, S., Dahlen, C., Berger, J., Riener, R., & Novak, V. H. V. (2023) · IEEE Transactions on Medical Robotics and Bionics · doi:10.1109/tmrb.2023.3321597 · Cited by 8 · see citing works

Validity of Accelerometry for Monitoring Real-World Arm Activity in Patients With Subacute Stroke: Evidence From the Extremity Constraint-Induced Therapy Evaluation Trial
Uswatte, G., Giuliani, C., Winstein, C., Zeringue, A., Hobbs, L., & Wolf, S. L. (2006) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2006.06.006 · Cited by 241 · see citing works
The use of accelerometer bracelets to evaluate arm motor function over a stroke rehabilitation period – an explorative observational study
Finn, E. L., Carlsson, H., Ericson, P., Åström, K., Brogårdh, C. B., & Wassélius, J. (2024) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01381-2 · Cited by 4 · see citing works
Relationships between arm and leg real-life activity and clinical assessments in individuals with disabling spasticity after stroke
Andersson, S., Danielsson, A., Sunnerhagen, K. S., & Murphy, M. A. (2026) · Frontiers in Stroke · doi:10.3389/fstro.2026.1731911
Sensitivity of the accelerometer as a measurement tool for upper extremity movement by stroke patients: a comparison with the action research arm test
Lee, J., Park, J., & Kim, Y.-J. (2015) · Journal of Physical Therapy Science · doi:10.1589/jpts.27.1053 · Cited by 11 · see citing works
Monitoring of Physical Activity after Stroke: A Systematic Review of Accelerometry-Based Measures
Gebruers, N., Vanroy, C., Truijen, S., Engelborghs, S., & De Deyn, P. P. (2010) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2009.10.025 · Cited by 293 · see citing works

Authors: van der Pas, S. C., Verbunt, J. A., Breukelaar, D. E., van Woerden, R., & Seelen, H. A.
Affiliations: Maastricht University (NL)
HAN University of Applied Sciences (NL)
Corresponding author: Verbunt, Jeanine A.
ORCID: Verbunt, Jeanine A.
Seelen, Henk A.
Venue: Archives of Physical Medicine and Rehabilitation
Publisher: Elsevier BV
Published: 2011-09
Volume: 92
Issue: 9
Pages: 1437-1442
ISSN: 0003-9993 (ISSN-L)
DOI: 10.1016/j.apmr.2011.02.021
OpenAlex: W2053812450
Cited by: 131
References: 26
Citations by year: 2026: 1 · 2025: 1 · 2024: 9 · 2023: 7 · 2022: 14 · 2021: 8 · 2020: 9 · 2019: 15 · 2018: 10 · 2017: 9 · 2016: 12 · 2015: 17 · 2014: 8 · 2013: 6 · 2012: 5
FWCI: 6.16
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Archives of Physical Medicine and Rehabilitation (publishedVersion)
PubMed (publishedVersion)
Research Publications (Maastricht University) (submittedVersion)
Topics: Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Health Sciences › Medicine › Physiology › Physical Activity and Health
Keywords: stroke, triaxial accelerometry, wrist-worn accelerometers, concurrent validity, discriminant validity, arm use, hand function, spasticity, stroke rehabilitation, Stroke Impact Scale
MeSH terms: Stroke Rehabilitation, Activities of Daily Living, Aged, Arm, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Motor Activity, Muscle, Skeletal, Stroke, Physical Therapy Modalities

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 ›

Are you an author, or do you see a problem with this page? Request a review

Assessment of Arm Activity Using Triaxial Accelerometry in Patients With a Stroke

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Cites

Cited by

Related

Record

About these checks