Soft Computing

, Volume 23, Issue 19, pp 9315–9326 | Cite as

Wearable devices for health-related quality of life evaluation

  • Adriano Tramontano
  • Mario Scala
  • Mario MagliuloEmail author


Medical and biomedical research fields are paying even closer attention to the health-related quality of life (HRQoL). Furthermore, having a precise snapshot of a subject’s daily life and of the related vital parameters (heart rate, ECG pattern, movement, sleeping habits, etc.) helps medical and social structures having a precise scenario of the elders. HRQoL is largely assessed by means of patient-reported outcomes (PROs), a flawed methodology if used for quality of life evaluation. Several kinds of biometrical parameters have been demonstrated to be significant in the evaluation of the HRQoL alongside with the PROs. It has also been shown that individual quality of life is tightly related to the patient frailty status (PFS). Pre-frail elders need a constant monitoring to catch any drift in their frailty markers for foretelling a possible shift in their PFS. A scalable hardware/software architecture has been realized with the aim of gathering vital parameters keeping low cumbersomeness. Systems should be able to gather, post-process and analyze monitored person’s vital parameters but, at the same time, patient therapies’ effectiveness can be constantly monitored and examined in deep. In the next future, the widely spreading of these systems will produce an huge quantity of structured, semi- or quasi-structured data. In order to reduce the complexity and manage such data, new storage techniques and new processing algorithms are desirable. Aim of this paper is to describe a novel architecture and an example of the algorithm to reduce the complexity of the non-structured data like a single-channel ECG.


Medical data processing Health monitoring Wearable devices Patient monitoring system Quality of life monitoring ECG recognition Frail elders 


Compliance with ethical standards

Conflict of interest

Authors Adriano Tramontano, Mario Scala and Mario Magliulo declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. Ahmed N, Mandel R, Fain MJ (2007) Frailty: an emerging geriatric syndrome. Am J Med 120(9):748–753CrossRefGoogle Scholar
  2. Allen PF (2003) Assessment of oral health related quality of life. Health Qual Life Outcomes 1(1):40CrossRefGoogle Scholar
  3. Baig MM, Gholamhosseini H (2013) Smart health monitoring systems: an overview of design and modeling. J Med Syst 37(2):9898CrossRefGoogle Scholar
  4. Basch EM et al (2011) Ev1 development of a guidance for including patient-reported outcomes (Pros) in post-approval clinical trials of oncology drugs for comparative effectiveness research (Cer). Value Health 14(3):A10CrossRefGoogle Scholar
  5. Bilotta C et al (2010) Dimensions and correlates of quality of life according to frailty status: a cross-sectional study on community-dwelling older adults referred to an outpatient geriatric service in Italy. Health Qual Life Outcomes 8(1):56MathSciNetCrossRefGoogle Scholar
  6. Centers for Disease Control and Prevention CDC, et al (2003) Trends in aging-United States and worldwide. MMWR 52(6):101Google Scholar
  7. Chand R, et al (2010) FPGA implementation of fast FIR low pass filter for EMG removal from ECG signal. In: 2010 international conference on power, control and embedded systems (ICPCES). IEEE, pp 1–5Google Scholar
  8. Chavan MS, Agarwala RA, Uplane MD (2008a) Interference reduction in ECG using digital FIR filters based on rectangular window. WSEAS Trans Signal Process 4(5):340–349Google Scholar
  9. Chavan MS, Agarwala RA, Uplane MD (2008b) Suppression of baseline wander and power line interference in ECG using digital IIR filter. Int J Circuits Syst Signal Process 2(2):356–365Google Scholar
  10. Christov II, Dotsinsky IA, Daskalov IK (1992) High-pass filtering of ECG signals using QRS elimination. Med Biol Eng Comput 30(2):253–256CrossRefGoogle Scholar
  11. Coale AJ (1989) Demographic transition. In: Eatwell J, Milgate M, Newman P (eds) Social economics. The New Palgrave. Palgrave Macmillan, LondonGoogle Scholar
  12. Correa AG et al (2007) Artifact removal from EEG signals using adaptive filters in cascade. J Phys Conf Ser 90:012081CrossRefGoogle Scholar
  13. De Pinto V (1992) Filters for the reduction of baseline wander and muscle artifact in the ECG. J Electrocardiol 25:40–48CrossRefGoogle Scholar
  14. Fried LP et al (2001) Frailty in older adults: evidence for a phenotype. J Gerontol Ser A Biol Sci Med Sci 56(3):M146–M157CrossRefGoogle Scholar
  15. Gao Z, et al. (2012) Design of ECG signal acquisition and processing system. In: 2012 international conference on biomedical engineering and biotechnology (iCBEB). IEEE, pp 762–764Google Scholar
  16. Gholam-Hosseini H, Nazeran H, Reynolds KJ (1998) ECG noise cancellation using digital filters. In: Proceedings of the 2nd international conference on bioelectromagnetism, 1998. IEEE, pp 151–152Google Scholar
  17. Gill TM et al (2006) Transitions between frailty states among community-living older persons. Arch Intern Med 166(4):418–423CrossRefGoogle Scholar
  18. Gobbens RJJ et al (2010) The Tilburg frailty indicator: psychometric properties. J Am Med Dir Assoc 11(5):344–355CrossRefGoogle Scholar
  19. Hogan DB (2018) Models, definitions, and criteria for frailty. In: Conn’s handbook of models for human aging, chap 3. Elsevier, pp 35–44.
  20. Husain AR (2002) Life expectancy in developing countries: a cross-section analysis. Bangladesh Dev Stud 28(1/2):161–178Google Scholar
  21. Jeon B, Lee J, Choi J (2013) Design and implementation of a wearable ECG system. Int J Smart Home 7(2):61–69Google Scholar
  22. Jevon P (2010) Procedure for recording a standard 12-lead electrocardiogram. Br J Nurs 19(10):649–651CrossRefGoogle Scholar
  23. Kakria P, Tripathi NK, Kitipawang P (2015) A real-time health monitoring system for remote cardiac patients using smartphone and wearable sensors. Int J Telemed Appl 2015:8Google Scholar
  24. Kaur M, et al (2011) Comparison of different approaches for removal of baseline wander from ECG signal. In: Proceedings of the international conference & workshop on emerging trends in technology. ACM. pp 1290–1294Google Scholar
  25. Lynn PA (1971) Recursive digital filters for biological signals. Med Biol Eng 9(1):37–43CrossRefGoogle Scholar
  26. Magliulo M, Tramontano A (2017) Cardiac monitoring of frail oncological outpatient using wearable devices. In: E-health and bioengineering conference (EHB), 2017. IEEE. pp 697–700Google Scholar
  27. Magliulo M, Cella L, Pacelli R (2012) Novel technique radio frequency identification (RFID) based to manage patient flow in a radiotherapy department. In: 2012 IEEE-EMBS international conference on biomedical and health informatics (BHI). IEEE pp. 972–975Google Scholar
  28. Magliulo M, Cella L, Pacelli R (2015) Bluetooth devices for the optimization of patients’ workflow in a radiation oncology department. In: E-health and bioengineering conference (EHB), 2015. IEEE, pp 1–4Google Scholar
  29. Mahmoud SA, Bamakhramah A, Al-Tunaiji SA (2013) Low-noise low-pass filter for ECG portable detection systems with digitally programmable range. Circuits Syst Signal Process 32(5):2029–2045MathSciNetCrossRefGoogle Scholar
  30. Mckee KJ, Houston DM, Barnes S (2002) Methods for assessing quality of life and well-being in frail older people. Psychol Health 17(3):737–751CrossRefGoogle Scholar
  31. Mckee K, et al (2005) Frailty, identity and the quality of later life. In: Understanding quality of life in old age, pp 117–129Google Scholar
  32. Mhaoláin AMN et al (2012) Frailty and quality of life for people with Alzheimer’s dementia and mild cognitive impairment. Am J Alzheimer’s Dis Other Dement 27(1):48–54CrossRefGoogle Scholar
  33. Mills GN, Homayoun H (1994) Wrist-worn ECG monitor. U.S. Patent No 5,289,824,Google Scholar
  34. Miura H et al (2010) Factors influencing oral health-related quality of life (OHRQoL) among the frail elderly residing in the community with their family. Arch Gerontol Geriatr 51(3):e62–e65CrossRefGoogle Scholar
  35. Moreno-Aguilar M et al (2013) The phenotype of frailty and health-related quality of life. J Frailty Aging 2(1):2–7Google Scholar
  36. Pal S, Mitra M (2012) Empirical mode decomposition based ECG enhancement and QRS detection. Comput Biol Med 42(1):83–92CrossRefGoogle Scholar
  37. Paul JS, Reddy MR, Kumar VJ (2000) A transform domain SVD filter for suppression of muscle noise artefacts in exercise ECG’s. IEEE Trans Biomed Eng 47(5):654–663CrossRefGoogle Scholar
  38. Pierleoni Paola et al (2014) An android-based heart monitoring system for the elderly and for patients with heart disease. Int J Telemed Appl 2014:10Google Scholar
  39. Ring L et al (2005) Response shift masks the treatment impact on patient reported outcomes (PROs): the example of individual quality of life in edentulous patients. Health Qual Life Outcomes 3(1):55CrossRefGoogle Scholar
  40. Robine J-M, Michel J-P (2004) Looking forward to a general theory on population aging. J Gerontol Ser A Biol Sci Med Sci 59(6):M590–M597CrossRefGoogle Scholar
  41. Rockwood K et al (1994) Frailty in elderly people: an evolving concept. CMAJ Can Med Assoc J 150(4):489Google Scholar
  42. Romero-ortuno R et al (2010) A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE). BMC Geriatr 10(1):57CrossRefGoogle Scholar
  43. Sankar AB, Kumar D, Seethalakshmi K (2010) Performance study of various adaptive filter algorithms for noise cancellation in respiratory signals. SPIJ 4(5):267Google Scholar
  44. Santos-Eggimann B et al (2008) The Lausanne cohort Lc65+: a population-based prospective study of the manifestations, determinants and outcomes of frailty. BMC Geriatr 8(1):20CrossRefGoogle Scholar
  45. Schwartz CE, Sprangers MAG (1999) Methodological approaches for assessing response shift in longitudinal health-related quality-of-life research. Social Sci Med 48(11):1531–1548CrossRefGoogle Scholar
  46. Strandberg TE, Pitkala KH (2007) Frailty in elderly people [editorial]. Lancet 369:1328–1329CrossRefGoogle Scholar
  47. Strawbridge WJ et al (1998) Antecedents of frailty over three decades in an older cohort. J Gerontol Ser B Psychol Sci Soc Sci 53(1):S9–S16CrossRefGoogle Scholar
  48. Sugiura Y et al (2010) Rapid increase in Japanese life expectancy after World War II. Biosci Trends 4(1):9–16Google Scholar
  49. Sun Y, Chan KL, Krishnan SM (2005) Characteristic wave detection in ECG signal using morphological transform. BMC Cardiovasc Disord 5(1):28CrossRefGoogle Scholar
  50. Suzuki M et al (2002) The relationship between fear of falling, activities of daily living and quality of life among elderly individuals. Nurs Health Sci 4(4):155–161CrossRefGoogle Scholar
  51. Tan KF, Chan KL, Choi K (2000) Detection of the QRS complex, P wave and T wave in electrocardiogram. In: 1st international conference on advances in medical signal and information processing, 2000 (IEE Conf. Publ. No. 476). IET, pp 41–47Google Scholar
  52. Tester S et al (2003) Exploring perceptions of quality of life of frail older people during and after their transition to institutional care ESRC Award Ref. L480254023Google Scholar
  53. Trahanias P, Skordalakis E (1989) Bottom-up approach to the ECG pattern-recognition problem. Med Biol Eng Comput 27(3):221–229CrossRefGoogle Scholar
  54. Uchmanowicz I, Gobbens RJJ (2015) The relationship between frailty, anxiety and depression, and health-related quality of life in elderly patients with heart failure. Clin Interv Aging 10:1595CrossRefGoogle Scholar
  55. Van Alste JA, Schilder TS (1985) Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps. IEEE Trans Biomed Eng 12:1052–1060CrossRefGoogle Scholar
  56. Van Alste JA, Van Eck W, Herrmann OE (1986) ECG baseline wander reduction using linear phase filters. Comput Biomed Res 19(5):417–427CrossRefGoogle Scholar
  57. Walston J (2004) Frailty-the search for underlying causes. Sci SAGE KE 2004(4):4Google Scholar
  58. Wen C et al (2008) Real-time ECG telemonitoring system design with mobile phone platform. Measurement 41(4):463–470CrossRefGoogle Scholar
  59. Wiklund I (2004) Assessment of patient-reported outcomes in clinical trials: the example of health-related quality of life. Fundam Clin Pharmacol 18(3):351–363MathSciNetCrossRefGoogle Scholar
  60. Woo J et al (2005) Social determinants of frailty. Gerontology 51(6):402–408CrossRefGoogle Scholar
  61. Yoshizawa M, et al (2010) A mobile communications system for home-visit medical services: the Electronic Doctor’s Bag. In: 2010 annual international conference of the IEEE engineering in medicine and biology. IEEE, pp 5496–5499Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Biostructure and Bioimaging Italian National Council of Research - CNRNaplesItaly

Personalised recommendations