期刊论文详细信息
Archives of Public Health
Smart wearable body sensors for patient self-assessment and monitoring
E Sander Connolly3  Olivier Bruyère1  Jean Yves Reginster1  Justin Slomian1  Randy D’Amico4  Brad E Zacharia3  Emmanuel LP Dumont2  Samuel S Bruce2  Mickey E Abraham3  Elvis Camacho3  Geoff Appelboom3 
[1]Department of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium and Support Unit in Epidemiology and Biostatistics, Department of Public Health Sciences, University of Liège, Liège, Belgium
[2]The Joan and Irwin Jacobs Technion-Cornell Innovation Institute, Cornell NYC Tech 111 8th Avenue #302, New York, NY 10011, USA
[3]Neurodigital Initiative, Columbia University, Department of Neurological Surgery, 630 West 168th Street, New York, NY 10032, USA
[4]Bartoli Brain Tumor Research Laboratory, Columbia University Irving Cancer Research Center Columbia University Medical Center, 1130 St. Nicholas Ave., New York, NY 10032, USA
关键词: Quantified patient;    Patient education;    eHealth;    Mobile health;    Sensors;   
Others  :  1070609
DOI  :  10.1186/2049-3258-72-28
 received in 2014-02-18, accepted in 2014-05-09,  发布年份 2014
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【 摘 要 】

Background

Innovations in mobile and electronic healthcare are revolutionizing the involvement of both doctors and patients in the modern healthcare system by extending the capabilities of physiological monitoring devices. Despite significant progress within the monitoring device industry, the widespread integration of this technology into medical practice remains limited. The purpose of this review is to summarize the developments and clinical utility of smart wearable body sensors.

Methods

We reviewed the literature for connected device, sensor, trackers, telemonitoring, wireless technology and real time home tracking devices and their application for clinicians.

Results

Smart wearable sensors are effective and reliable for preventative methods in many different facets of medicine such as, cardiopulmonary, vascular, endocrine, neurological function and rehabilitation medicine. These sensors have also been shown to be accurate and useful for perioperative monitoring and rehabilitation medicine.

Conclusion

Although these devices have been shown to be accurate and have clinical utility, they continue to be underutilized in the healthcare industry. Incorporating smart wearable sensors into routine care of patients could augment physician-patient relationships, increase the autonomy and involvement of patients in regards to their healthcare and will provide for novel remote monitoring techniques which will revolutionize healthcare management and spending.

【 授权许可】

   
2014 Appelboom et al.; licensee BioMed Central Ltd.

【 预 览 】
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【 参考文献 】
  • [1]Ricciardi L, Mostashari F, Murphy J, Daniel JG, Siminerio EP: A national action plan to support consumer engagement via e-health. Health Aff (Millwood) 2013, 32:376-84.
  • [2]Say R, Murtagh M, Thomson R: Patients’ preference for involvement in medical decision making: a narrative review. Patient Educ Couns 2006, 60(2):102-114.
  • [3]Hayakawa M, Uchimura Y, Omae K, Waki K, Fujita H, Ohe K: A smartphone-based medication self-management system with realtime medication monitoring. Appl Clin Inform 2013, 4:37-52.
  • [4]Swan M: Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int J Environ Res Public Health 2009, 6:492-525.
  • [5]Chen KY, Bassett DR: The technology of accelerometry-based activity monitors: current and future. Med Sci Sports Exerc 2005, 37:S490-S500.
  • [6]Dobkin BH, Dorsch A: The promise of mHealth: daily activity monitoring and outcome assessments by wearable sensors. Neurorehabil Neural Repair 2011, 25(9):788-798.
  • [7]Darwish A, Hassanien AE: Wearable and Implantable wireless sensor network solutions for healthcare monitoring. Sensors 2011, 11(6):5561-5595.
  • [8]CDC—chronic disease prevention and health promotion [http://www.cdc.gov/fmo/topic/budget%20information/factsheets/CHRONIC_Factsheet.pdf webcite]
  • [9]Bonato P: Advances in wearable technology and its medical applications. Conf Proc IEEE Eng Med Biol Soc 2010, 2010:2021-2024.
  • [10]Cook DJ, Thompson JE, Prinsen SK, Dearani JA, Deschamps C: Functional recovery in the elderly after major surgery: assessment of mobility recovery using wireless technology. Ann Thorac Surg 2013, 96:1057-61.
  • [11]Yang C-C, Hsu Y-L: A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 2010, 10(8):7772-7788.
  • [12]Chan M, Estève D, Fourniols J-Y, Escriba C, Campo E: Smart wearable systems: current status and future challenges. Artif Intell Med 2012, 56(3):137-156.
  • [13]Mathie MJ, Coster ACF, Lovell NH, Celler BG: Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol Meas 2004, 25:R1-R20.
  • [14]Luinge HJ, Veltink PH: Measuring orientation of human body segments using miniature gyroscopes and accelerometers. Med Biol Eng Comput 2005, 43:273-282.
  • [15]Yang C-C, Hsu Y-L: Development of a wearable motion detector for telemonitoring and real-time identification of physical activity. Telemed J E Health 2009, 15:62-72.
  • [16]Montgomery-Downs HE, Insana SP, Bond JA: Movement toward a novel activity monitoring device. Sleep Breath 2012, 16(3):913-917.
  • [17]Sekine M, Tamura T, Togawa T, Fukui Y: Classification of waist-acceleration signals in a continuous walking record. Med Eng Phys 2000, 22:285-291.
  • [18]Karantonis DM, Narayanan MR, Mathie M, Lovell NH, Celler BG: Implementation of a Real-Time Human Movement Classifier Using a Triaxial Accelerometer for Ambulatory Monitoring. 2006, 10:156-167.
  • [19]Simone LK, Sundarrajan N, Luo X, Jia Y, Kamper DG: A low cost instrumented glove for extended monitoring and functional hand assessment. J Neurosci Methods 2007, 160:335-348.
  • [20]Wu YC, Chen P-F, Hu ZA, Chang CH, Lee GC, Yu WC: A mobile health monitoring system using RFID ring-type pulse sensor [abstract]. Dependable, Autonomic and Secure Computing 2009, 1:317.
  • [21]Rhoads FA, Grandner J: Assessment of an aural infrared sensor for body temperature measurement in children. Clin Pediatr (Phila) 1990, 29:112-115.
  • [22]Pandian PS, Mohanavelu K, Safeer KP, Kotresh TM, Shakunthala DT, Gopal P, Padaki VC: Smart vest: wearable multi-parameter remote physiological monitoring system. Med Eng Phys 2008, 30:466-477.
  • [23]Sardini E, Serpelloni M: T-shirt for vital parameter monitoring. Lect Notes Electr Eng 2014, 162:201-205.
  • [24]Geoff A, Eric S, Pierre R, Yves J, Jean-Yves Reginster ESC: A critical assessment of approaches to outpatient monitoring. Curr Med Res Opin 2014, 30:1-2.
  • [25]Ton V-K, Martin SS, Blumenthal RS, Blaha MJ: Comparing the new European cardiovascular disease prevention guideline with prior American heart association guidelines: an editorial review. Clin Cardiol 2013, 36:E1-6.
  • [26]World Health Organization[http://www.who.int/chp/chronic_disease_report/full_report.pdf webcite]
  • [27]Fuster V, Kelly B: Promoting Cardiovascular Health in the Developing World: A Critical Challenge to Achieve Global Health. 2010.
  • [28]Chandrasekara V: Measuring Vital Signs Using Smart Phones. Denton, Texas: University of North Texas; 2010.
  • [29]Weber S, Scharfschwerdt P, Seel T, Kertzscher U, Affeld K: Continuous wrist blood pressure measurement with ultrasound. Biomed Tech 2013, 58:1-2.
  • [30]Scheffler M, Hirt E: Wearable devices for telemedicine applications. J Telemed Telecare 2005, 11(Suppl 1):11-14.
  • [31]Lindemann U, Hock A, Stuber M, Keck W, Becker C: Evaluation of a fall detector based on accelerometers: a pilot study. Med Biol Eng Comput 2005, 43:548-551.
  • [32]Kuo Y-L, Culhane KM, Thomason P, Tirosh O, Baker R: Measuring distance walked and step count in children with cerebral palsy: an evaluation of two portable activity monitors. Gait Posture 2009, 29:304-310.
  • [33]Lukowicz P, Anliker U, Ward J, Troster G, Hirt E, Neufelt C: AMON: a wearable medical computer for high risk patients. Proceedings Sixth Int Symp Wearable Comput 2002, 133-134.
  • [34]Poon CCY, Zhang YT: Cuff-less and noninvasive measurements of arterial blood pressure by pulse transit time. Conf Proc IEEE Eng Med Biol Soc 2005, 6:5877-5880.
  • [35]Poon CCYPCCY, Wong YMWYM, Zhang Y-TZY-T: M-Health: the development of cuff-less and wearable blood pressure meters for use in body sensor networks. 2006 IEEE/NLM Life Sci Syst Appl Work 2006, 1-2.
  • [36]Murata Manufacturing Company [http://www.murata.com/ webcite]
  • [37]Paul G, David A, Dwight Reynolds A: Accuracy and novelty of an inexpensive iPhone-based event recorder [abstract]. Heart Rhythm 2012. sp23
  • [38]Saxon LA: Ubiquitous wireless ECG recording: a powerful tool physicians should embrace. J Cardiovasc Electrophysiol 2013, 24:480-483.
  • [39]Paton C, Hansen M, Fernandez-Luque L, YS L a: Self-Tracking, social media and personal health records for patient empowered self-care. contribution of the IMIA social media working group. Yearb Med Inform 2012, 7:16-24.
  • [40]Nagae D, Mase A: Measurement of heart rate variability and stress evaluation by using microwave reflectometric vital signal sensing. Rev Sci Instrum 2010, 81:094301.
  • [41]Dokhan B, Setz C, Arnrich B, Töster G: Monitoring passenger’s breathing - a feasibility study. Swiss Soc Biomed Eng Annu Meet 2007, 1:1.
  • [42]Universal biosensors [http://www.universalbiosensors.com/Products.aspx webcite]
  • [43]Rao A, Hou P, Golnik T, Flaherty J, Vu S: Evolution of data management tools for managing self-monitoring of blood glucose results: a survey of iPhone applications. J diabetes Sci Technol 2010, 4:949-957.
  • [44]Leelarathna L, English SW, Thabit H, Caldwell K, Allen JM, Kumareswaran K, Wilinska ME, Nodale M, Haidar A, Evans ML, Burnstein R, Hovorka R: Accuracy of subcutaneous continuous glucose monitoring in critically ill adults: improved sensor performance with enhanced calibrations. Diabetes Technol Ther 2014, 16:97-101.
  • [45]Zanon M, Sparacino G, Facchinetti A, Riz M, Talary MS, Suri RE, Caduff A, Cobelli C: Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the multisensor system. Med Biol Eng Comput 2012, 50(10):1047-1057.
  • [46]Kovatchev BP, Renard E, Cobelli C, Zisser HC, Keith-Hynes P, Anderson SM, Brown SA, Chernavvsky DR, Breton MD, Farret A, Pelletier M-J, Place J, Bruttomesso D, Del Favero S, Visentin R, Filippi A, Scotton R, Avogaro A, Doyle FJ: Feasibility of outpatient fully integrated closed-loop control: first studies of wearable artificial pancreas. Diabetes Care 2013, 36:1851-8.
  • [47]Zhang J, Hodge W, Hutnick C, Wang X: Noninvasive diagnostic devices for diabetes through measuring tear glucose. J diabetes Sci Technol 2011, 5:166-172.
  • [48]Forbes [http://www.forbes.com/sites/ptc/2014/02/12/google-contacts-will-help-diabetics-monitor-blood-sugar-via-tears/ webcite]
  • [49]Baram Y, Lenger R: Gait improvement in patients with cerebral palsy by visual and auditory feedback. Neuromodulation 2012, 15:48-52. discussion 52
  • [50]Lockman J, Fisher RS, Olson DM: Detection of seizure-like movements using a wrist accelerometer. Epilepsy Behav 2011, 20:638-641.
  • [51]Rand D, Eng JJ, Tang P-F, Jeng J-S, Hung C: How active are people with stroke?: use of accelerometers to assess physical activity. Stroke 2009, 40:163-168.
  • [52]Kirste T, Hoffmeyer A, Koldrack P, Bauer A, Schubert S, Schröder S, Teipel S: Detecting the effect of Alzheimer’s disease on everyday motion behavior. J Alzheimers Dis 2014, 38:121-32.
  • [53]Weiss A, Sharifi S, Plotnik M, van Vugt JPP, Giladi N, Hausdorff JM: Toward automated, at-home assessment of mobility among patients with Parkinson disease, using a body-worn accelerometer. Neurorehabil Neural Repair 2011, 25(9):810-818.
  • [54]Jovanov E, Milenkovic A, Otto C, de Groen PC: A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. J Neuroeng Rehabil 2005, 2:6. BioMed Central Full Text
  • [55]Bonnie S, Basia B, Kevin C, Catherine W, Jeff Coppersmith JH: Bodies in motion: monitoring daily activity and exercise with motion sensors in people with chronic pulmonary disease. J Rehabil Dev 2003, 40:45.
  • [56]Wagenaar RC, Sapir I, Zhang Y, Markovic S, Vaina LM, Little TDC: Continuous monitoring of functional activities using wearable, wireless gyroscope and accelerometer technology. Annu Int Conf IEEE Eng Med Biol Soc 2011, 2011:4844-4847.
  • [57]Fulk G, Combs SA, Danks KA, Nirider CD, Bhavana Raja DSR: Accuracy of 2 activity monitors in detecting steps in people with stroke and traumatic brain injury. Phys Ther 2014, 94:222-229.
  • [58]Bassett DR, John D: Use of pedometers and accelerometers in clinical populations: validity and reliability issues. Phys Ther Rev 2010, 15(3):135-142.
  • [59]Daniel Olguín O, Alex P: Social Sensors for Automatic Data Collection. In Proceedings of the Fourteenth Americas Conference on Information Systems. Toronto; 14-17 August 2008:14.
  • [60]Morillo DS, Rojas Ojeda JL, Crespo Foix LF, Jiménez AL: An accelerometer-based device for sleep apnea screening. IEEE Trans Inf Technol Biomed 2010, 14:491-499.
  • [61]Wicks P, Stamford J, Grootenhuis MA, Haverman L, Ahmed S: Innovations in e-health. Qual Life Res 2014, 23:195-203.
  • [62]Bergmann JHM, McGregor AH: Body-worn sensor design: what do patients and clinicians want? Ann Biomed Eng 2011, 39:2299-2312.
  • [63]Bergmann JHM, Chandaria V, McGregor A: Wearable and implantable sensors: the patient’s perspective. Sensors (Basel) 2012, 12:16695-709.
  • [64]Chan M, Estève D, Escriba C, Campo E: A review of smart homes- present state and future challenges. Comput Methods Programs Biomed 2008, 91:55-81.
  • [65]2014 medicare changes expand coverage for telemedicine [http://mhcc.dhmh.maryland.gov/hit/telemedicine/Documents/telemedicine_2014medicarechanges_summary.pdf webcite]
  • [66]John Percival JH: Big brother or brave new world? Telecare and its implications for older people’s independence and social inclusion. Crit Soc Policy 2006, 26:888-909.
  • [67]Steele R, Lo A, Secombe C, Wong YK: Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare. Int J Med Inform 2009, 78:788-801.
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