Exploring the Parkinson patients' perspective on home-based video recording for movement analysis: a qualitative study

Attitudes Toward the Adoption of Remote Patient Monitoring and Artificial Intelligence in Parkinson's Disease Management: Perspectives of Patients and Neurologists

OBJECTIVE

Early detection of Parkinson's Disease (PD) progression remains a challenge. As remote patient monitoring solutions (RMS) and artificial intelligence (AI) technologies emerge as potential aids for PD management, there's a gap in understanding how end users view these technologies. This research explores patient and neurologist perspectives on AI-assisted RMS.

METHODS

Qualitative interviews and focus-groups were conducted with 27 persons with PD (PwPD) and six neurologists from Finland and Italy. The discussions covered traditional disease progression detection and the prospects of integrating AI and RMS. Sessions were recorded, transcribed, and underwent thematic analysis.

RESULTS

The study involved five individual interviews (four Italian participants and one Finnish) and six focus-groups (four Finnish and two Italian) with PwPD. Additionally, six neurologists (three from each country) were interviewed. Both cohorts voiced frustration with current monitoring methods due to their limited real-time detection capabilities. However, there was enthusiasm for AI-assisted RMS, contingent upon its value addition, user-friendliness, and preservation of the doctor-patient bond. While some PwPD had privacy and trust concerns, the anticipated advantages in symptom regulation seemed to outweigh these apprehensions.

DISCUSSION

The study reveals a willingness among PwPD and neurologists to integrate RMS and AI into PD management. Widespread adoption requires these technologies to provide tangible clinical benefits, remain user-friendly, and uphold trust within the physician-patient relationship.

CONCLUSION

This study offers insights into the potential drivers and barriers for adopting AI-assisted RMS in PD care. Recognizing these factors is pivotal for the successful integration of these digital health tools in PD management.

Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes

ABSTRACT

Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson's disease and essential tremor) is rapidly increasing. Current diagnosis and monitoring of these disorders rely largely on face-to-face assessments utilising clinical rating scales, which are semi-subjective and time-consuming. To address these challenges, the utilisation of artificial intelligence (AI) has emerged. This review explores the advantages and challenges associated with using AI-driven video monitoring to care for elderly patients with movement disorders. The AI-based video monitoring systems offer improved efficiency and objectivity in remote patient monitoring, enabling real-time analysis of data, more uniform outcomes and augmented support for clinical trials. However, challenges, such as video quality, privacy compliance and noisy training labels, during development need to be addressed. Ultimately, the advancement of video monitoring for movement disorders is expected to evolve towards discreet, home-based evaluations during routine daily activities. This progression must incorporate data security, ethical considerations and adherence to regulatory standards.

Video Recording Patients for Direct Care Purposes: Systematic Review and Narrative Synthesis of International Empirical Studies and UK Professional Guidance

BACKGROUND

Video recordings of patients may offer advantages to supplement patient assessment and clinical decision-making. However, little is known about the practice of video recording patients for direct care purposes.

OBJECTIVE

We aimed to synthesize empirical studies published internationally to explore the extent to which video recording patients is acceptable and effective in supporting direct care and, for the United Kingdom, to summarize the relevant guidance of professional and regulatory bodies.

METHODS

Five electronic databases (MEDLINE, Embase, APA PsycINFO, CENTRAL, and HMIC) were searched from 2012 to 2022. Eligible studies evaluated an intervention involving video recording of adult patients (≥18 years) to support diagnosis, care, or treatment. All study designs and countries of publication were included. Websites of UK professional and regulatory bodies were searched to identify relevant guidance. The acceptability of video recording patients was evaluated using study recruitment and retention rates and a framework synthesis of patients' and clinical staff's perspectives based on the Theoretical Framework of Acceptability by Sekhon. Clinically relevant measures of impact were extracted and tabulated according to the study design. The framework approach was used to synthesize the reported ethico-legal considerations, and recommendations of professional and regulatory bodies were extracted and tabulated.

RESULTS

Of the 14,221 abstracts screened, 27 studies met the inclusion criteria. Overall, 13 guidance documents were retrieved, of which 7 were retained for review. The views of patients and clinical staff (16 studies) were predominantly positive, although concerns were expressed about privacy, technical considerations, and integrating video recording into clinical workflows; some patients were anxious about their physical appearance. The mean recruitment rate was 68.2% (SD 22.5%; range 34.2%-100%; 12 studies), and the mean retention rate was 73.3% (SD 28.6%; range 16.7%-100%; 17 studies). Regarding effectiveness (10 studies), patients and clinical staff considered video recordings to be valuable in supporting assessment, care, and treatment; in promoting patient engagement; and in enhancing communication and recall of information. Observational studies (n=5) favored video recording, but randomized controlled trials (n=5) did not demonstrate that video recording was superior to the controls. UK guidelines are consistent in their recommendations around consent, privacy, and storage of recordings but lack detailed guidance on how to operationalize these recommendations in clinical practice.

CONCLUSIONS

Video recording patients for direct care purposes appears to be acceptable, despite concerns about privacy, technical considerations, and how to incorporate recording into clinical workflows. Methodological quality prevents firm conclusions from being drawn; therefore, pragmatic trials (particularly in older adult care and the movement disorders field) should evaluate the impact of video recording on diagnosis, treatment monitoring, patient-clinician communication, and patient safety. Professional and regulatory documents should signpost to practical guidance on the implementation of video recording in routine practice.

TRIAL REGISTRATION

PROSPERO CRD42022331825: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=331825.

Successful implementation of technology in the management of Parkinson's disease: Barriers and facilitators

Background

Parkinson's disease (PD) is a progressive neurodegenerative disease with a fast increasing prevalence. Several pharmacological and non-pharmacological interventions are available to alleviate symptoms. Technology can be used to improve the efficiency, accessibility and feasibility of these treatments. Although many technologies are available, only few are actually implemented in daily clinical practice.

Aim

Here, we study the barriers and facilitators, as experienced by patients, caregivers and/or healthcare providers, to successful implement technology for PD management.

Methods

We performed a systematic literature search in the PubMed and Embase databases until June 2022. Two independent raters screened the titles, abstracts and full texts on: 1) people with PD; 2) using technology for disease management; 3) qualitative research methods providing patients', caregivers and/or healthcare providers' perspective, and; 4) full text available in English or Dutch. Case studies, reviews and conference abstracts were excluded.

Results

We found 5420 unique articles of which 34 were included in this study. Five categories were made: cueing (n = 3), exergaming (n = 3), remote monitoring using wearable sensors (n = 10), telerehabilitation (n = 8) and remote consultation (n = 10). The main barriers reported across categories were unfamiliarity with technology, high costs, technical issues and (motor) symptoms hampering the use of some technologies. Facilitators included good usability, experiencing beneficial effects and feeling safe whilst using the technology.

Conclusion

Although only few articles presented a qualitative evaluation of technologies, we found some important barriers and facilitators that may help to bridge the gap between the fast developing technological world and actual implementation in day-to-day living with PD.

Ethical and Legal Aspects of Technology-Assisted Care in Neurodegenerative Disease

Technological solutions are increasingly seen as a way to respond to the demands of managing complex chronic conditions, especially neurodegenerative diseases such as Parkinson’s Disease. All of these new possibilities provide a variety of chances to improve the lives of affected persons and their families, friends, and caregivers. However, there are also a number of challenges that should be considered in order to safeguard the interests of affected persons. In this article, we discuss the ethical and legal considerations associated with the use of technology-assisted care in the context of neurodegenerative conditions.

Acceptability of an In-Home Multimodal Sensor Platform in Parkinson’s Disease: A Qualitative Study (Preprint)

Background

Parkinson disease (PD) symptoms are complex, gradually progressive, and fluctuate hour by hour. Home-based technological sensors are being investigated to measure symptoms and track disease progression. A smart home sensor platform, with cameras and wearable devices, could be a useful tool to use to get a fuller picture of what someone’s symptoms are like. High-resolution video can capture the ground truth of symptoms and activities. There is a paucity of information about the acceptability of such sensors in PD.

Objective

The primary objective of our study was to explore the acceptability of living with a multimodal sensor platform in a naturalistic setting in PD. Two subobjectives are to identify any suggested limitations and to explore the sensors’ impact on participant behaviors.

Methods

A qualitative study was conducted with an inductive approach using semistructured interviews with a cohort of PD and control participants who lived freely for several days in a home-like environment while continuously being sensed.

Results

This study of 24 participants (12 with PD) found that it is broadly acceptable to use multimodal sensors including wrist-worn wearables, cameras, and other ambient sensors passively in free-living in PD. The sensor that was found to be the least acceptable was the wearable device. Suggested limitations on the platform for home deployment included camera-free time and space. Behavior changes were noted by the study participants, which may have related to being passively sensed. Recording high-resolution video in the home setting for limited periods of time was felt to be acceptable to all participants.

Conclusions

The results broaden the knowledge of what types of sensors are acceptable for use in research in PD and what potential limitations on these sensors should be considered in future work. The participants’ reported behavior change in this study should inform future similar research design to take this factor into account. Collaborative research study design, involving people living with PD at every stage, is important to ensure that the technology is acceptable and that the data outcomes produced are ecologically valid and accurate.

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2020-041303

Sensors for Context-Aware Smart Healthcare: A Security Perspective

The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.

The state of telemedicine for persons with Parkinson's disease

PURPOSE OF REVIEW

The COVID-pandemic has facilitated the implementation of telemedicine in both clinical practice and research. We highlight recent developments in three promising areas of telemedicine: teleconsultation, telemonitoring, and teletreatment. We illustrate this using Parkinson's disease as a model for other chronic neurological disorders.

RECENT FINDINGS

Teleconsultations can reliably administer parts of the neurological examination remotely, but are typically not useful for establishing a reliable diagnosis. For follow-ups, teleconsultations can provide enhanced comfort and convenience to patients, and provide opportunities for blended and proactive care models. Barriers include technological challenges, limited clinician confidence, and a suboptimal clinician-patient relationship. Telemonitoring using wearable sensors and smartphone-based apps can support clinical decision-making, but we lack large-scale randomized controlled trials to prove effectiveness on clinical outcomes. Increasingly many trials are now incorporating telemonitoring as an exploratory outcome, but more work remains needed to demonstrate its clinical meaningfulness. Finding a balance between benefits and burdens for individual patients remains vital. Recent work emphasised the promise of various teletreatment solutions, such as remotely adjustable deep brain stimulation parameters, virtual reality enhanced exercise programs, and telephone-based cognitive behavioural therapy. Personal contact remains essential to ascertain adherence to teletreatment.

SUMMARY

The availability of different telemedicine tools for remote consultation, monitoring, and treatment is increasing. Future research should establish whether telemedicine improves outcomes in routine clinical care, and further underpin its merits both as intervention and outcome in research settings.

Machine Learning-Based Automatic Rating for Cardinal Symptoms of Parkinson Disease

OBJECTIVE

We developed and investigated the feasibility of a machine learning-based automated rating for the 2 cardinal symptoms of Parkinson disease (PD): resting tremor and bradykinesia.

METHODS

Using OpenPose, a deep learning-based human pose estimation program, we analyzed video clips for resting tremor and finger tapping of the bilateral upper limbs of 55 patients with PD (110 arms). Key motion parameters, including resting tremor amplitude and finger tapping speed, amplitude, and fatigue, were extracted to develop a machine learning-based automatic Unified Parkinson's Disease Rating Scale (UPDRS) rating using support vector machine (SVM) method. To evaluate the performance of this model, we calculated weighted κ and intraclass correlation coefficients (ICCs) between the model and the gold standard rating by a movement disorder specialist who is trained and certified by the Movement Disorder Society for UPDRS rating. These values were compared to weighted κ and ICC between a nontrained human rater and the gold standard rating.

RESULTS

For resting tremors, the SVM model showed a very good to excellent reliability range with the gold standard rating (κ 0.791; ICC 0.927), with both values higher than that of nontrained human rater (κ 0.662; ICC 0.861). For finger tapping, the SVM model showed a very good reliability range with the gold standard rating (κ 0.700 and ICC 0.793), which was comparable to that for nontrained human raters (κ 0.627; ICC 0.797).

CONCLUSION

Machine learning-based algorithms that automatically rate PD cardinal symptoms are feasible, with more accurate results than nontrained human ratings.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that machine learning-based automated rating of resting tremor and bradykinesia in people with PD has very good reliability compared to a rating by a movement disorder specialist.

The Use of Telehealth to Enhance Care in ALS and other Neuromuscular Disorders

Telehealth has the potential to improve the efficiency of healthcare while reducing the burden on patients and caregivers. Encounters can be synchronous or asynchronous. When used for care of those with amyotrophic lateral sclerosis (ALS) by individual health care providers or by a multidisciplinary team, synchronous telehealth is feasible, acceptable, may produce outcomes comparable to those of in-person care, and is cost effective. Individuals with ALS who use telehealth tend to have lower physical and respiratory function and to live farther from an ALS clinic than those who exclusively attend in-person clinic visits. Asynchronous telehealth can be used as a substitute full multidisciplinary visits, or for remote monitoring of pulmonary function, gait/falls, and speech. Barriers to implementing telehealth on a wider scale include disparities in access to technology and challenges surrounding medical licensure and billing, but these are being addressed.

The Role of Engagement in Teleneurorehabilitation: A Systematic Review

The growing understanding of the importance of involving patients with neurological diseases in their healthcare routine either for at-home management of their chronic conditions or after the hospitalization period has opened the research for new rehabilitation strategies to enhance patient engagement in neurorehabilitation. In addition, the use of new digital technologies in the neurorehabilitation field enables the implementation of telerehabilitation systems such as virtual reality interventions, video games, web-based interventions, mobile applications, web-based or telephonic telecoach programs, in order to facilitate the relationship between clinicians and patients, and to motivate and activate patients to continue with the rehabilitation process at home. Here we present a systematic review that aims at reviewing the effectiveness of different engagement strategies and the different engagement assessments while using telerehabilitation systems in patients with neurological disorders. We used PICO's format to define the question of the review, and the systematic review protocol was designed following the Preferred Reported Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Bibliographical data was collected by using the following bibliographic databases: PubMed, EMBASE, Scopus, and Web of Science. Eighteen studies were included in this systematic review for full-text analyses. Overall, the reviewed studies using engagement strategies through telerehabilitation systems in patients with neurological disorders were mainly focused on patient self-management and self-awareness, patient motivation, and patient adherence subcomponents of engagement, that are involved in by the behavioral, cognitive, and emotional dimensions of engagement. Conclusion: The studies commented throughout this systematic review pave the way for the design of new telerehabilitation protocols, not only focusing on measuring quantitative or qualitative measures but measuring both of them through a mixed model intervention design (1). The future clinical studies with a mixed model design will provide more abundant data regarding the role of engagement in telerehabilitation, leading to a possibly greater understanding of its underlying components.

The Impact of a Novel Immersive Virtual Reality Technology Associated with Serious Games in Parkinson's Disease Patients on Upper Limb Rehabilitation: A Mixed Methods Intervention Study

BACKGROUND

Parkinson's disease is a neurodegenerative disorder that causes impaired motor functions. Virtual reality technology may be recommended to optimize motor learning in a safe environment. The objective of this paper was to evaluate the effects of a novel immersive virtual reality technology used for serious games (Oculus Rift 2 plus leap motion controller-OR2-LMC) for upper limb outcomes (muscle strength, coordination, speed of movements, fine and gross dexterity). Another objective was to obtain qualitative data for participants' experiences related to the intervention.

METHODS

A mixed methods intervention (embedded) study was used, with a qualitative design after a technology intervention (quantitative design). The intervention and qualitative design followed international guidelines and were integrated into the method and reporting subheadings.

RESULTS

Significant improvements were observed in strength (p = 0.028), fine (p = 0.026 to 0.028) and gross coordination dexterity, and speed movements (p = 0.039) in the affected side, with excellent compliance (100%) and a high level of satisfaction (3.66 ± 0.18 points out of the maximum of 4). No adverse side effects were observed. Qualitative findings described patients' perspectives regarding OR2-LMC treatment, facilitators and barriers for adherence, OR2-LMC applications, and treatment improvements.

CONCLUSIONS

The intervention showed positive results for the upper limbs, with elements of discordance, expansion, and confirmation between qualitative and quantitative results.