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. 2019 Nov 29;19(23):5258.
doi: 10.3390/s19235258.

A Secure Occupational Therapy Framework for Monitoring Cancer Patients' Quality of Life

Md Abdur Rahman  1 , Md Mamunur Rashid  2 , Julien Le Kernec  3   4   5 , Bruno Philippe  6 , Stuart J Barnes  2 , Francesco Fioranelli  3 , Shufan Yang  3 , Olivier Romain  4 , Qammer H Abbasi  3 , George Loukas  7 , Muhammad Imran  3
Affiliations

A Secure Occupational Therapy Framework for Monitoring Cancer Patients' Quality of Life

Md Abdur Rahman et al. Sensors (Basel). .

Abstract

Once diagnosed with cancer, a patient goes through a series of diagnosis and tests, which are referred to as "after cancer treatment". Due to the nature of the treatment and side effects, maintaining quality of life (QoL) in the home environment is a challenging task. Sometimes, a cancer patient's situation changes abruptly as the functionality of certain organs deteriorates, which affects their QoL. One way of knowing the physiological functional status of a cancer patient is to design an occupational therapy. In this paper, we propose a blockchain and off-chain-based framework, which will allow multiple medical and ambient intelligent Internet of Things sensors to capture the QoL information from one's home environment and securely share it with their community of interest. Using our proposed framework, both transactional records and multimedia big data can be shared with an oncologist or palliative care unit for real-time decision support. We have also developed blockchain-based data analytics, which will allow a clinician to visualize the immutable history of the patient's data available from an in-home secure monitoring system for a better understanding of a patient's current or historical states. Finally, we will present our current implementation status, which provides significant encouragement for further development.

Keywords: cyber-physical occupational therapy system; distributed medical big data; health IoT sensors; quality of life; therapeutic kinematic data.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Relationship between quality of life and cancer treatment plan concerning different factors (such as occupational therapy) affecting the quality of life.
Figure 2
Figure 2
High-level occupational therapy use cases to assist in quality of life (QoL).
Figure 3
Figure 3
Therapist and patient can visualize the performance of the prescribed occupational therapy (OT) by looking at overall QoL data and functional status of the patient. HR QoL: health-related quality of life.
Figure 4
Figure 4
High-level software components of the occupational therapy environment to assist a cancer patient’s quality of life enhancement.
Figure 5
Figure 5
High-level sensory component diagram of the occupational therapy environment to assist cancer patient’s QoL.
Figure 6
Figure 6
High-level blockchain and off-chain storage for securely sharing OT data.
Figure 7
Figure 7
Example of a permissioned, multidimensional chain of a private blockchain to store cancer patients’ QoL data.
Figure 8
Figure 8
Occupation therapy exercise in a smart home appliance control scenario.
Figure 9
Figure 9
Salient components in a smart contract to support IoT-based quality of life within the home environment.
Figure 10
Figure 10
Game-based OT therapy exercise design: (a) gesture-based flying, (b) gesture-based jewel mining, (c) gesture-based map browsing, and (d) live skeletal data sharing with an authorized therapist.
Figure 11
Figure 11
Guided OT exercise through augmented reality view.
Figure 12
Figure 12
Guided OT Exercise through telecollaboration view.
Figure 13
Figure 13
A therapist in the cyber world guides a subject in the physical world using a virtual reality view.
Figure 14
Figure 14
Virtual model therapist rendered as skeletal pose guides a subject.
Figure 15
Figure 15
(a) Annotation window; and (b) analytic window.
Figure 16
Figure 16
(a) Full body skeletal tracking sensor; and (b) RF sensing for assisted living—activity and vital sign monitoring.
Figure 17
Figure 17
Hand skeletal tracking sensors (a) Spatial field of view of the LEAP motion sensor (b) Spatial field of view of the MYO EMG sensor.
Figure 18
Figure 18
User interface of range of motion (ROM) BOT Digital Twin.
Figure 19
Figure 19
User Interface of ROM BOT Digital Twin, with the therapist either physically collocated or through remote collaboration: (a) both patient and the therapist are on the same physical proximity; (b) Therapist and the patient are at two separate locations but they can collaborate via the live sensory data sharing framework.
Figure 20
Figure 20
Implementation testbed: (a) Medical Internet of Things (IoT) devices connected to blockchain at the edge network; and (b) distributed application that securely shows the IoT device status extracted from the blockchain.
Figure 21
Figure 21
Quality-of-life data collected from sensory media and visualized from blockchain and off-chain data explorer: (a) live gait analysis to support occupational therapy and (b) semantic sensory data analytics.
Figure 22
Figure 22
(a) Testing based on 5000 transactions made on five different instances of throughput measurement, and (b) testing based on 5000 transactions made on five different instances of latency measurement.
See this image and copyright information in PMC

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