Development and validation of a wearable sensing platform for assessment of patients undergoing breast and axillary surgery
File(s)
Author(s)
Che Bakri, Nur Amalina
Type
Thesis
Abstract
Patient-reported outcomes are commonly used to evaluate upper limb (UL) morbidities following breast cancer surgery. Although they help to gauge patients' views of their UL function, these assessments are primarily subjective and susceptible to recall or response bias. Objective outcome tools, such as goniometry, can be used to measure range of motion. Nevertheless, these measurements are prone to inter-operator variability, necessitate periodic evaluation, and can be time-consuming in clinical environments. The aim of this thesis was to develop and validate the use of wearable activity monitors (WAMs) to provide postoperative monitoring options for patients undergoing breast/axillary surgery.
This work evolved from an initial feasibility study in a healthy cohort and a breast cancer cohort undergoing breast/axillary surgery to a larger cohort of breast cancer survivors with a long-term follow-up. UL activity was assessed preoperatively, postoperatively on the inpatient ward and on discharge home for up to 2 weeks, as well as at greater than 6 months postoperatively. Activity data provided insight into patients' baseline UL activity, as well as their recovery following different types of breast surgeries. Further detailed analysis revealed that preoperative activity and the magnitude of short-term UL activity measured by WAMs may predict for longer term UL activity (>6 months). The qualitative evaluation demonstrated that patients were satisfied with this monitoring method and that the majority of patients believed that these systems could improve engagement in physiotherapy.
This thesis has made significant contributions to the field of study by developing a new WAM methodology and testing them under clinically relevant conditions. The findings of this research can be applied by researchers/clinicians aiming to employ wearable technologies for continuous and objective patient monitoring, as well as for developing personalised rehabilitation strategies. Implementing these technologies has the potential to improve the quality and cost-effectiveness of managing UL morbidities.
This work evolved from an initial feasibility study in a healthy cohort and a breast cancer cohort undergoing breast/axillary surgery to a larger cohort of breast cancer survivors with a long-term follow-up. UL activity was assessed preoperatively, postoperatively on the inpatient ward and on discharge home for up to 2 weeks, as well as at greater than 6 months postoperatively. Activity data provided insight into patients' baseline UL activity, as well as their recovery following different types of breast surgeries. Further detailed analysis revealed that preoperative activity and the magnitude of short-term UL activity measured by WAMs may predict for longer term UL activity (>6 months). The qualitative evaluation demonstrated that patients were satisfied with this monitoring method and that the majority of patients believed that these systems could improve engagement in physiotherapy.
This thesis has made significant contributions to the field of study by developing a new WAM methodology and testing them under clinically relevant conditions. The findings of this research can be applied by researchers/clinicians aiming to employ wearable technologies for continuous and objective patient monitoring, as well as for developing personalised rehabilitation strategies. Implementing these technologies has the potential to improve the quality and cost-effectiveness of managing UL morbidities.
Version
Open Access
Date Issued
2024-10-03
Date Awarded
01/07/2025
License URL
Advisor
Leff, Daniel
Darzi, Ara
Kwasnicki, Richard
Sponsor
Imperial College London
National Institute for Health Research (Great Britain)
Grant Number
WSSS_P69945
WSGG_PA3152
Publisher Department
Department of Medicine
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)