Wrist ROM measurements using smartphone photography: Reliability and validity

Smartphone-Based Hand Function Assessment: Systematic Review

BACKGROUND

Hand function assessment heavily relies on specific task scenarios, making it challenging to ensure validity and reliability. In addition, the wide range of assessment tools, limited and expensive data recording, and analysis systems further aggravate the issue. However, smartphones provide a promising opportunity to address these challenges. Thus, the built-in, high-efficiency sensors in smartphones can be used as effective tools for hand function assessment.

OBJECTIVE

This review aims to evaluate existing studies on hand function evaluation using smartphones.

METHODS

An information specialist searched 8 databases on June 8, 2023. The search criteria included two major concepts: (1) smartphone or mobile phone or mHealth and (2) hand function or function assessment. Searches were limited to human studies in the English language and excluded conference proceedings and trial register records. Two reviewers independently screened all studies, with a third reviewer involved in resolving discrepancies. The included studies were rated according to the Mixed Methods Appraisal Tool. One reviewer extracted data on publication, demographics, hand function types, sensors used for hand function assessment, and statistical or machine learning (ML) methods. Accuracy was checked by another reviewer. The data were synthesized and tabulated based on each of the research questions.

RESULTS

In total, 46 studies were included. Overall, 11 types of hand dysfunction-related problems were identified, such as Parkinson disease, wrist injury, stroke, and hand injury, and 6 types of hand dysfunctions were found, namely an abnormal range of motion, tremors, bradykinesia, the decline of fine motor skills, hypokinesia, and nonspecific dysfunction related to hand arthritis. Among all built-in smartphone sensors, the accelerometer was the most used, followed by the smartphone camera. Most studies used statistical methods for data processing, whereas ML algorithms were applied for disease detection, disease severity evaluation, disease prediction, and feature aggregation.

CONCLUSIONS

This systematic review highlights the potential of smartphone-based hand function assessment. The review suggests that a smartphone is a promising tool for hand function evaluation. ML is a conducive method to classify levels of hand dysfunction. Future research could (1) explore a gold standard for smartphone-based hand function assessment and (2) take advantage of smartphones' multiple built-in sensors to assess hand function comprehensively, focus on developing ML methods for processing collected smartphone data, and focus on real-time assessment during rehabilitation training. The limitations of the research are 2-fold. First, the nascent nature of smartphone-based hand function assessment led to limited relevant literature, affecting the evidence's completeness and comprehensiveness. This can hinder supporting viewpoints and drawing conclusions. Second, literature quality varies due to the exploratory nature of the topic, with potential inconsistencies and a lack of high-quality reference studies and meta-analyses.

Introducing a Simple Tool of Patient Self-Assessment of Wrist Range of Motion

Hand disorders can reduce wrist range of motion (ROM). The SARS-CoV-2 pandemic highlighted challenges in routine follow-up exams, making telemedicine a viable solution. This study evaluates the feasibility and accuracy of patient self-measured wrist ROM using a self-designed goniometer template. The template was designed to measure flexion/extension and radial/ulnar abduction movements. A cohort of 50 adults (25 males/25 females) participated in this prospective study. The exclusion criteria included wrist immobilization and ages outside of 18-65 years. Participants self-assessed their wrist ROM with the goniometer template. Measurements were independently performed by a student and a specialist using standard goniometry, as well as a resident using the self-designed goniometer. The results were blinded for unbiased analysis. Mean differences in ROM varied across movement directions, with minimal differences for ulnar abduction and more substantial deviations for radial abduction, extension and flexion. The patient-specialist comparison showed deviations below 5 degrees for flexion and ulnar abduction in 50% of cases. Telemedicine, expanded by the COVID-19 pandemic, offers significant potential for hand rehabilitation. Current methods of ROM assessment lack cost-effectiveness and simplicity. Our method, demonstrating comparable accuracy for most movements, provides a cost-effective, reliable alternative for remote ROM assessment, enhancing telemedicine practices in hand rehabilitation.

The Validity and Reliability of a Smartphone Application for Measuring Wrist and Metacarpophalangeal Joint Motion

Background Accurate measurement of the range of motion (ROM) is crucial for guiding upper extremity rehabilitation. Inaccurate measurements can mislead clinicians and harm patient compliance. This study aimed to evaluate the validity and reliability of a smartphone application (Angulus) for measuring wrist and metacarpophalangeal (MCP) joint ROM. Methodology This study included 64 volunteers with no prior wrist injuries. The wrist flexion/extension, radial/ulnar deviation, and MCP joint flexion/extension ROM were assessed by an experienced physiotherapist (Assessor 1) using the Angulus and a standard two-arm goniometer. The validity of Angulus was evaluated by correlating it with the goniometer measurements using the Pearson correlation coefficient. For the reliability analysis, an inexperienced biomedical engineer (Assessor 2) performed the same measurements using Angulus twice in different sessions, in addition to Assessor 1. The intra-rater and inter-rater reliability were tested using the intraclass correlation coefficient. Results The mean age of the participants was 29.5 ± 8.2 years, with 62% being female. The validity of the Angulus app measurements was indicated by the adequate to excellent correlation between the Angulus and goniometer measurements (ranging from 0.44 to 0.81). The intra-rater reliability of the Angulus app was excellent for Assessor 1 (ranging from 0.76 to 0.90) and adequate to excellent for Assessor 2 (ranging from 0.71 to 0.88). The inter-rater reliability of Angulus was excellent (ranging from 0.91 to 0.96). Conclusions Angulus is a valid and reliable method to measure the wrist and MCP joint ROM.

Telerehabilitation Technology Used for Remote Wrist/Finger Range of Motion Evaluation: A Scoping Review

Background

Monitoring finger/wrist range of motion (ROM) is an important component of routine hand therapy after surgery. Telerehabilitation is a field that may potentially address various barriers of in-person hand therapy appointments. Therefore, the purpose of this scoping review is to identify telerehabilitation technologies that can be feasibly used in a patient's home to objectively measure finger/wrist ROM.

Methods

Following PRISMA-ScR guidelines for scoping reviews, we systematically searched MEDLINE and Embase electronic databases using alternative word spellings for the following core concepts: "wrist/hand," "rehabilitation," and "telemedicine." Studies were imported into Covidence, and systematic two-level screening was done by two independent reviewers. Patient demographics and telerehabilitation information were extracted from the selected articles, and a narrative synthesis of the findings was done.

Results

There were 28 studies included in this review, of which the telerehabilitation strategies included smartphone angle measurement applications, smartphone photography, videoconference, and wearable or external sensors. Most studies measured wrist ROM with the most accurate technologies being wearable and external sensors. For finger ROM, the smartphone angle application and photography had higher accuracy than sensor systems. The telerehabilitation strategies that had the highest level of usability in a remote setting were smartphone photographs and estimation during virtual appointments.

Conclusions

Telerehabilitation can be used as a reliable substitute to in-person goniometer measurements, particularly the smartphone photography and motion sensor ROM measurement technologies. Future research should investigate how to improve the accuracy of motion sensor applications that are available on easy-to-access devices.

Development of Joint Activity Angle Measurement and Cloud Data Storage System

In this study, we developed a range of motion sensing system (ROMSS) to simulate the function of the elbow joint, with errors less than 0.76 degrees and 0.87 degrees in static and dynamic verification by the swinging and angle recognition modules, respectively. In the simulation process, the ɣ correlation coefficient of the Pearson difference between the ROMSS and the universal goniometer was 0.90, the standard deviations of the general goniometer measurements were between ±2 degrees and ±2.6 degrees, and the standard deviations between the ROMSS measurements were between ±0.5 degrees and ±1.6 degrees. With the ROMSS, a cloud database was also established; the data measured by the sensor could be uploaded to the cloud database in real-time to provide timely patient information for healthcare professionals. We also developed a mobile app for smartphones to enable patients and healthcare providers to easily trace the data in real-time. Historical data sets with joint activity angles could be retrieved to observe the progress or effectiveness of disease recovery so the quality of care could be properly assessed and maintained.

Validation of a smartphone application and wearable sensor for measurements of wrist motions

We developed a smartphone application to measure wrist motion using the mobile device's built-in motion sensors or connecting it via Bluetooth to a wearable sensor. Measurement of wrist motion with this method was assessed in 33 participants on two occasions and compared with those obtained with a standard goniometer. The test-retest reproducibility in healthy individuals ranged from good to excellent (intraclass correlation (ICC) 0.76-0.95) for all motions, both with and without the wearable sensor. These results improved to excellent (ICC 0.90-0.96) on the second test day, suggesting a learning effect. The day-to-day reproducibility was overall better with the wearable sensor (mean ICC 0.87) compared with the application without using sensor or goniometer (mean ICC 0.82 and 0.60, respectively). This study suggests that smartphone-based measurements of wrist range of motion are feasible and highly accurate, making it a powerful tool for outcome studies after wrist surgery.

The Telemedicine-Based Pediatric Examination of the Neck and Upper Limbs: A Narrative Review

With the COVID-19 pandemic hastening the adoption of telemedicine into clinical practice, it has also prompted an abundance of new literature highlighting its capabilities and limitations. The purpose of this review is to summarize the current state of the literature on telemedicine applied in the context of a musculoskeletal examination of the neck and upper limbs for children 3 to 18 years old. The PubMed and ScienceDirect databases were searched for relevant articles from January 2015 to August 2021 using a combination of keywords and nested searches. General examination components including inspection, guided self-palpation, range of motion, sensory and motor examination, as well as special testing are described. Although the literature is focused mainly on adult populations, we describe how each component of the exam can be reliably incorporated into a virtual appointment specific to pediatric patients. Caregivers are generally needed for most consultations, but certain maneuvers can be self-performed by older children and adolescents alone. There is general feasibility, validity, and substantial reliability in performing most examination components of the upper limbs remotely, except for the shoulder exam. Compared to those made in person, clinical diagnoses established virtually were found to be either the same or similar in most cases, and management decisions also had high agreement. Despite this, there is evidence that some pediatric providers may not be able to collect all the information needed from a telemedicine visit to make a complete clinical assessment. Lastly, currently available smartphone applications measuring joint range of motion were found to have high reliability and validity. This narrative review not only establishes a foundation for a structured pediatric musculoskeletal examination, but also aims to increase physicians' confidence in incorporating telemedicine into their standard of care.

The Delivery of Orthopaedic Care midst COVID-19 and Social Distancing

In this paper we present the findings of a literature review covering articles published in the last three decades describing the application of telemedicine in orthopaedics. A review of the PubMed Central and Medline provided 75 articles studying the role of telemedicine, the majority directly examining the application of telemedicine in orthopaedic patients. We report the summarized findings of these studies, the financial and HIPAA considerations of using telemedicine, and provide an example of our single urban level-1 trauma center's strategy for incorporating telemedicine into the clinical practice of orthopaedic surgeons during the COVID-19 pandemic.