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A Sensor Based Assessment Monitoring System for Patients with Neurological Disabilities

Lu Bai

Abstract


The neurological conditions can cause the disability of upper limb and the rehabilitation therapy can help the patients to restore their upper limb motion. However, the current method for upper limb rehabilitation assessment is very basic. The aim of this work is to develop a system and visualize the information to support the doctors and clinicians in the assessment of upper limb motion of patients who are undertaken neurological rehabilitation. Movement tracking including position and orientation have been tracked and data analysis have been done in both time domain and frequency domain. Furthermore, movement smoothness analysis has been done to obtain more information from patients’ movement recovery. The created information visualization can provide objective measurements of patients’ motion recovery and insightful information and for doctors and clinicians including the frequency analysis and movement smoothness analysis. The findings showed the system is able to provide accurate position within 0.1 cm and orientation tracking within 1 degree and meaningful insights for the assessment of upper limb motion functions in daily rehabilitation assessment by providing doctors and clinicians with visualizations of the objective measurements.

Keywords


upper limb rehabilitation; inertial sensing; information visualization; wearable sensors

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References


The Neurological Alliance, Neuro numbers, 2004.

P. Langhorne, J. Bernhardt, G. Kwakkel, Stroke rehabilitation, Lancet. (2011). https://doi.org/10.1016/S0140-6736(11)60325-5.

A. Pollock, S.E. Farmer, M.C. Brady, P. Langhorne, G.E. Mead, J. Mehrholz, F. van Wijck, Interventions for improving upper limb function after stroke, Cochrane Database Syst. Rev. (2014). https://doi.org/10.1002/14651858.CD010820.pub2.

A. Houwink, R.H. Nijland, A.C. Geurts, G. Kwakkel, Functional recovery of the paretic upper limb after stroke: Who regains hand capacity?, Arch. Phys. Med. Rehabil. (2013). https://doi.org/10.1016/j.apmr.2012.11.031.

Z. Zhang, Q. Fang, X. Gu, Objective assessment of upper-limb mobility for poststroke rehabilitation, IEEE Trans. Biomed. Eng. (2016). https://doi.org/10.1109/TBME.2015.2477095.

N. Nordin, S.Q. Xie, B. Wünsche, Assessment of movement quality in robot- Assisted upper limb rehabilitation after stroke: A review, J. Neuroeng. Rehabil. (2014). https://doi.org/10.1186/1743-0003-11-137.

A.R. Fugl Meyer, L. Jaasko, I. Leyman, The post stroke hemiplegic patient. I. A method for evaluation of physical performance, Scand. J. Rehabil. Med. (1975).

J.H. Carr, R.B. Shepherd, L. Nordholm, D. Lynne, Investigation of a new motor assessment scale for stroke patients, Phys. Ther. (1985). https://doi.org/10.1093/ptj/65.2.175.

R.W. Bohannon, M.B. Smith, Interrater reliability of a modified Ashworth scale of muscle spasticity, Phys. Ther. (1987). https://doi.org/10.1093/ptj/67.2.206.

A. Filippeschi, N. Schmitz, M. Miezal, G. Bleser, E. Ruffaldi, D. Stricker, Survey of motion tracking methods based on inertial sensors: A focus on upper limb human motion, Sensors (Switzerland). (2017). https://doi.org/10.3390/s17061257.

C. Yang, A. Kerr, V. Stankovic, L. Stankovic, P. Rowe, S. Cheng, Human Upper Limb Motion Analysis for Post-Stroke Impairment Assessment Using Video Analytics, IEEE Access. (2016). https://doi.org/10.1109/ACCESS.2016.2523803.

A.O. Bǎlan, L. Sigal, M.J. Black, A quantitative evaluation of video-based 3D person tracking, in: Proc. - 2nd Jt. IEEE Int. Work. Vis. Surveill. Perform. Eval. Track. Surveillance, VS-PETS, 2005. https://doi.org/10.1109/VSPETS.2005.1570935.

H. Zhou, T. Stone, H. Hu, N. Harris, Use of multiple wearable inertial sensors in upper limb motion tracking, Med. Eng. Phys. (2008). https://doi.org/10.1016/j.medengphy.2006.11.010.

B. Hingtgen, J.R. McGuire, M. Wang, G.F. Harris, An upper extremity kinematic model for evaluation of hemiparetic stroke, J. Biomech. (2006). https://doi.org/10.1016/j.jbiomech.2005.01.008.

J.C. Perry, J. Rosen, S. Burns, Upper-limb powered exoskeleton design, in: IEEE/ASME Trans. Mechatronics, 2007. https://doi.org/10.1109/TMECH.2007.901934.

L. Bai, M.G. Pepper, Y. Yan, S.K. Spurgeon, M. Sakel, M. Phillips, A multi-parameter assessment tool for upper limb motion in neurorehabilitation, in: Conf. Rec. - IEEE Instrum. Meas. Technol. Conf., 2011. https://doi.org/10.1109/IMTC.2011.5944169.

L. Bai, M.G. Pepper, Y. Yan, S.K. Spurgeon, M. Sakel, M. Phillips, Quantitative Assessment of Upper Limb Motion in Neurorehabilitation Utilizing Inertial Sensors, IEEE Trans. Neural Syst. Rehabil. Eng. (2015). https://doi.org/10.1109/TNSRE.2014.2369740.

G.M. Moreira, L.H.F. Giovanini, M.P.R. de Castro, G.N. Nogueira, T.C. Boumer, E.F. Manffra, Filtering motion signals from Microsoft Kinect® in the context of stroke rehabilitation, Res. Biomed. Eng. (2019). https://doi.org/10.1007/s42600-019-00029-8.

C. Zerpa, C. Lees, P. Patel, E. Pryzsucha, The Use of Microsoft Kinect for Human Movement Analysis, Int. J. Sport. Sci. (2015).

Y. Tian, X. Meng, D. Tao, D. Liu, C. Feng, Upper limb motion tracking with the integration of IMU and Kinect, Neurocomputing. (2015). https://doi.org/10.1016/j.neucom.2015.01.071.

S. Giancola, A. Corti, F. Molteni, R. Sala, Motion capture: An evaluation of kinect V2 body tracking for upper limb motion analysis, in: Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, 2017. https://doi.org/10.1007/978-3-319-58877-3_39.

L. Bai, M.G. Pepper, Y. Yana, S.K. Spurgeon, M. Sakel, Application of low cost inertial sensors to human motion analysis, in: 2012 IEEE I2MTC - Int. Instrum. Meas. Technol. Conf. Proc., 2012. https://doi.org/10.1109/I2MTC.2012.6229349.

L. Bai, M.G. Pepper, Y. Yan, M. Phillips, M. Sakel, Low Cost Inertial Sensors for the Motion Tracking and Orientation Estimation of Human Upper Limbs in Neurological Rehabilitation, IEEE Access. (2020). https://doi.org/10.1109/ACCESS.2020.2981014.

Lu Bai, Matthew G Pepper, Yong Yan, Malcolm Phillips, Mohamed Sakel, Inertial sensor based quantitative assessment of upper limb range of motion and functionality before and after botulinum toxin: a pilot study, Glob. J. Eng. Technol. Adv. (2020). https://doi.org/10.30574/gjeta.2020.2.3.0008.

L. Bai, M.G. Pepper, Y. Yan, M. Phillips, M. Sakel, Quantitative measurement of upper limb motion pre- and post-treatment with Botulinum Toxin, Meas. J. Int. Meas. Confed. (2021). https://doi.org/10.1016/j.measurement.2020.108304.

L. Bai, M. Pepper, Y. Yan, S.K. Spurgeon, M. Sakel, M. Phillips, Quantitative Assessment of Limb Motion by Inertial Sensors Before and After Botulinum Toxin for Spasticity, Arch. Phys. Med. Rehabil. (2014). https://doi.org/10.1016/j.apmr.2014.07.205.

J.J. Craig, Manipulator-Mechanism Design, in: Introd. to Robot. Mech. Control, 2005.

A. Lawrence, Modern Inertial Technology: Navigation, Guidance, and Control, 2nd ed, Mod. Inert. Technol. (1998).

J. Jankovic, J. Beach, K. Schwartz, C. Contant, Tremor and longevity in relatives of patients with parkinson’s disease, essential tremor, and control subjects, Neurology. (1995). https://doi.org/10.1212/WNL.45.4.645.

B. Rohrer, S. Fasoli, H.I. Krebs, R. Hughes, B. Volpe, W.R. Frontera, J. Stein, N. Hogan, Movement smoothness changes during stroke recovery, J. Neurosci. (2002). https://doi.org/10.1523/jneurosci.22-18-08297.2002.

L. Dipietro, H.I. Krebs, S.E. Fasoli, B.T. Volpe, N. Hogan, Submovement changes characterize generalization of motor recovery after stroke, Cortex. (2009). https://doi.org/10.1016/j.cortex.2008.02.008.

N. Hogan, D. Sternad, Sensitivity of smoothness measures to movement duration, amplitude, and arrests, J. Mot. Behav. (2009). https://doi.org/10.3200/35-09-004-RC.

C.C. Tsao, M.M. Mirbagheri, Upper limb impairments associated with spasticity in neurological disorders, J. Neuroeng. Rehabil. (2007). https://doi.org/10.1186/1743-0003-4-45.

E.Z. Tronick, L. Fetters, K.L. Olson, Y. Chen, Similar and Functionally Typical Kinematic Reaching Parameters in 7- and 15-Month-Old in Utero Cocaine-Exposed and Unexposed Infants, Dev. Psychobiol. (2004). https://doi.org/10.1002/dev.20002.




DOI: https://doi.org/10.18196/jrc.26127

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