Intelligent Robotics for Elderly Assistance in Hong Kong (i-REACH)

Hong Kong is facing a significant societal challenge - a rapidly aging society. The proportion of the population aged 65 and over in Hong Kong increased from 16.6% in 2005 to 20.1% in 2020. The number of people aged 65 or older worldwide is estimated to reach 1.6 billion by 2050. In terms of quality of life, a major difficulty that many older people experience is a severe limitation in mobility and manipulability in their daily life, resulting in tremendous social and economic challenges. Hence, the investigators propose to develop innovative intelligent robotics systems to improve mobility and manipulability, prevent falls, enhance independence, and improve the quality of life of older adults. In particular, the investigators propose a User-Centric Co-creation (UC3) approach to developing novel intelligent wearable robots to enhance mobility and manipulability. The UC3 approach will start with a psycho-social study to identify the individual needs of older adults for achieving mobility and manipulability, which then leads to determining kinesiology-based design parameters for personalized wearable robots. The robots will be developed based on novel hybrid soft/rigid structures integrated with intelligent sensors, distributed actuators, and cooperative control methods. The robotic devices will be tested with elderly users in a user- user-centric environment for evaluation and continuous improvement. The investigators have conducted preliminary studies of the proposed approach. The results of the preliminary studies have clearly shown the feasibility as well as the novelty of the proposed approach. It can be stated confidently that our multidisciplinary team of experts in engineering, gerontology and medicine will be able to work with the elderly community and potential users to successfully deliver the project objectives. Furthermore, an Impact Committee, consisting of leaders in Hong Kong's elder community, elderly care organizations and related industries, has been proposed. It will advise and facilitate the research team to ensure the maximum impact of the research results and successful technology transfer. Commercialization efforts will be embedded in every phase of the project to ensure that the results will both benefit the elderly community and contribute to the economic development of Hong Kong. The outcomes of this project will place Hong Kong at the frontier of global robotics research and technology, provide critical technology to transform the elderly care services in Hong Kong, and create opportunities for training the next generation of scientists and engineers in robotics technology in Hong Kong.

Study Overview

• Status: Recruiting
• Conditions: Sarcopenia
• Intervention / Treatment: Device: Intelligent robotics for elderly assistance - sarcopenia

Detailed Description

This study aims to provide an intelligent robotic solution for assisting older adults' mobility and manipulability. Using a novel UC3 development approach, the investigators will systematically study the requirements of elderly users to formulate technical specifications for designing personalized wearable robotic systems. Specifically, we will develop: (1) a novel UC3 development approach to identify the requirements and constraints for the elderly's mobility and manipulability based on gerontechnological and physiological studies; (2) a personalized sensor-driven wearable robot for elderly assistance; (3) an integrated interactive testing system to support the development of intelligent robot-enabled elderly assistance, and to significantly improve performance and safety; and (4) an experimental environment to test, evaluate and demonstrate the developed systems, emphasizing significantly improvement of the mobility and manipulability of older adults.

In order to improve human mobility and manipulability, a wearable robotic device is required to have certain rigidity to support the human body or sustain an external load. Inspired by the flexibility of multiple muscle bundles in biological muscle tissues, the investigators propose to use multiple servomotors to form distributed driving joints of the wearable robot of a hybrid structure and to regulate the driving force and speed of joints by coordinating the output of each motor in real-time. The UC3 approach starts with a psycho-social study and leads to the identification of the critical needs of older adults described by kinesiology-based design parameters. This will provide the guidelines for developing intelligent elderly assistive robots by integrating novel hybrid soft/rigid soft wearable robots, an intelligent sensing system and control methods. The robots will then be tested and evaluated in a user-centric environment to enable the next phase of improvement. Our systems will be developed based on requirements at three levels: (1) the physiology level, involving individual active elements; (2) the function level of action; and (3) the behaviour level of performing tasks.

In order to inform the design of our wearable robotic device, it is essential to understand the needs and compensation requirements of the elderly users in their daily life at physiology, function, and behaviour levels. 60 elderly subjects will be recruited for examination. The user needs assessment will result in a list of categories of "movement, tasks, and behaviour" with the scenarios of "mobility problems in the home and the community" that older people think important and necessary to complete independently daily life. Based on the psycho-social studies and physical and physiological tests done in laboratory testing and evaluation platform, the investigators will conduct needs and compensation assessments quantitatively to formulate technical requirements for system design and development. Furthermore, as the measured data continue to accumulate, the investigators will develop machine learning methods to efficiently estimate reliable compensation schemes based on a small set of measured data on a new user. This will greatly accelerate the efficiency of compensation studies when the number of users increases.

To evaluate our wearable devices for improvement, the investigators will quantitatively assess the enhancement of the mobility and manipulability of the targeted elderly using a pre-and post-implementation experiment. A total of 180 older people from the out-patient clinics and/or elderly community service units will be recruited for user studies in three phases, with 60 people in each phase. Subjects to be recruited in Phase 2 and Phase 3 need to meet the following inclusion and exclusion criteria: (1) aged 65 or older; (2) SARC-F score (measurement of sarcopenia) equal to or over 4; (3) SPPB score less than 11; (4) moderate mobility impairment, i.e., ADL between 6 and 12; (5) capable of clear communication; and (6) no cognitive impairment. The participants will use the robotics system and integrated environment to perform daily self-care to uncover problems in functionality, usability, and acceptance of the robotic device prototype. The system, connected to mobile apps and the Internet, will serve as a platform to measure and record data on how the participants engage in pre-specified activities. The experiment will last six months, and the outcome will be assessed pre-and post-implementation for comparison and validation. The major testing criteria include the design specifications for functionalities and reliability, user experiences, system security and privacy. Participants' perceived ability and confidence to perform daily self-care activities, quality of life, and acceptance of the system will also be measured. The first stage of evaluation will focus on the functionality and reliability of the individual system, measuring the gait stability using walker tipping index, fatigability by handle reaction vector (HRV), and centre of gravity. The second stage will focus on evaluating the system performance and usability of the IAE.

The participation of the older adults recruited from the out-patient clinics and/or elderly community service units in the tests, surveys, and/or interviews will not affect the quality of care they are receiving. No drug usage and medical treatment will be involved in the study. Intervention, surveys, and/or interviews do not impose any physical or medical risk to participants. The only concern is that participants may feel a little tired after the tests. Participants can voluntarily withdraw from the study at any time, without giving any reasons, their medical care or original rights will not be affected.

The investigators will conduct the following analysis to suit the project needs: user analysis, physiological analysis, and robotic system development. Concerning user analysis, chi-square or independent t-tests will be used to examine the differences in the baseline characteristics between older adults with different levels of mobility and manipulability difficulties. Further, the investigators will conduct regression analysis to compare the difference in outcomes between older adults with different levels of mobility and manipulability difficulties. Recruitment rate, drop-out rate and missing data will also be examined and reported. Concerning physiological analysis, the investigators will conduct muscle anatomical analysis, motion analysis, gait analysis, foot pressure analysis, and electromyography analysis. Concerning robotic system development, the investigators will conduct analysis related to sensors development and performance.

The principal investigator will be responsible for keeping of the personal data during and after the study. The data containing personal identifiers will be kept 5 years after the publication of the first paper arising from the research project and the anonymized data will be kept 10 years after the publication of the first paper arising from the project. All information obtained will be used for research purposes only. All the data will be stored in an encrypted workstation and on password-protected online cloud storage.

• Study Type: Interventional
• Enrollment (Anticipated): 180
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Vivian W.Q. Lou, PhD; Phone Number: 2831-5334/3917-4835; Email: wlou@hku.hk

Study Locations

• Hong Kong
  • Hong Kong, Hong Kong, 999777
    • Recruiting
    • The University of Hong Kong
    • Contact: Clio. Y.M. Cheng; Phone Number: 2831-5227; Email: cliocym@connect.hku.hk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years to 75 years (OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Reference group participants:

Inclusion Criteria:

• Aged 65 or older
• SARC-F score (measurement of sarcopenia) below 4
• Capable of clear communication
• No cognitive impairment

Exclusion Criteria:

• Osteoporosis
• A history of the spine, knee, hip, and ankle joint surgery

Intervention group participants:

Inclusion Criteria:

• Aged 65 or older
• SARC-F score (measurement of sarcopenia) equal to or over 4
• Able to perform the experiment in a laboratory setting independently
• Capable of clear communication
• No cognitive impairment

Exclusion Criteria:

• Osteoporosis
• A history of the spine, knee, hip, and ankle joint surgery.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: SUPPORTIVE_CARE
• Allocation: NA
• Interventional Model: SINGLE_GROUP
• Masking: NONE

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

EXPERIMENTAL: Intervention Group; Older adults without mobility and/or manipulability difficulties will be treated as reference group while older adults with mobility and/or manipulability difficulties will use the robotics system and integrated environment to perform daily self-care.

Device: Intelligent robotics for elderly assistance - sarcopenia; Participants will use the robotics system and integrated environment to perform daily self-care to uncover problems in functionality, usability, and acceptance of the robotic device prototype. The system, connected to mobile apps and the Internet, will serve as a platform to measure and record data on how the participants engage in pre-specified activities. The experiment will last six months, and the outcome will be assessed pre- and post-implementation for comparison and validation. The major testing criteria include the design specifications for functionalities and reliability, user experiences, system security and privacy.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Lower extremity functioning	Lower extremity functioning will be assessed by the short physical performance battery (SPPB). SPPB is a group of measures that combines the results of the gait speed, chair stand and balance tests. The scores range from 0 (worst performance) to 12 (best performance). The total score of the gait speed test ranged from 0 (unable to walk) to 4 (if time is less than 4.82 sec). The total score of the chair stand test ranged from 0 (unable to complete 5 chair stands or completes stand in > 60 sec) to 4 (if chair stand time is 11.19 sec or less). In the balance test, the participants will perform a total of three balance tests. First, the side-by-side stand, ranging from 0 (not attempted / not held for 10 sec) to 1 (held for 10 sec). Second, the semi-tandem stand, ranging from 0 (not attempted / not held for 10 sec) to 1 (held for 10 sec). Third, the tandem stand, ranging from 0 (not attempted / held < 3 sec) to 2 (held for 10 sec).	6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Maximum handgrip strength	Maximum handgrip strength will be assessed based on the following procedures. The investigator will prepare the Jamar Smart Digital Hand Dynamometer or the Baseline 12-0286 Electronic Smedly Hand Dynamometer to conduct the handgrip strength test. The investigators will measure the maximum handgrip strength of each hand three times, alternatively. The investigators will record the largest strength among all six attempts and regard it as the maximum handgrip strength. The unit of measurement is kg.	6 months
Knee Maximum Voluntary Contraction (MVC)	Knee Maximum Voluntary Contraction (MVC) will be assessed based on the following procedures. The investigators will use a knee extension machine by VITOX Fitness with a hand-held dynamometer (HHD) by Lafayette Instrument (model 01165) fixed on the pole contacting the anterior of the tibial bone, at 50-100mm above the lateral malleolus. The investigators will measure the MVC using the HHD of each leg independently twice to identify the weaker leg. Next, the investigators will instruct the participants to perform the isometric knee extension test on the weaker leg and measured MVC using HDD at four knee angles (i.e. 90°, 66°, 42°, and 18°). The unit of measurement is kgf.	6 months
Gait motion analysis - cadence, step length, stride length, opposite foot contact and foot off	A total of five parameters of gait motion analysis will be measured, including including (a) cadence (step/s), (b) step length (cm), (c) stride length (cm), (d) opposite foot contact (%), and (e) foot off (%). Cadence or walking rate is calculated in steps per second3. Step length is the distance between the point of initial contact of one foot and the point of initial contact of the opposite foot. Stride length is the distance between successive points of initial contact of the same foot. Opposite foot contact is the heel of the opposite foot contacts the ground while the toes of the reference foot still touch the ground, providing double support. Foot off is the moment when the heel begins to lift off the ground in preparation for forwarding propulsion of the body.	6 months
Balance ability	Balance ability will be measured by an in-house developed balance sensor that can measure dynamic force distribution under human feet. This balance sensor operates on an optical principle called Frustrated Total Internal Reflection (FTIR), which has been widely applied to develop haptic sensors for robots. Force distribution under feet will be recorded in images by a camera installed in the balance sensor, hence the force distribution variation information is encoded in a video. The variance from the mean centre during balance testing will be used as an indicator of balance ability.	6 months

Collaborators and Investigators

• Sponsor: The University of Hong Kong

Study record dates

Study Major Dates

• Study Start (ACTUAL): November 1, 2020
• Primary Completion (ANTICIPATED): June 30, 2025
• Study Completion (ANTICIPATED): October 30, 2025

Study Registration Dates

• First Submitted: March 25, 2022
• First Submitted That Met QC Criteria: April 6, 2022
• First Posted (ACTUAL): April 14, 2022

Study Record Updates

• Last Update Posted (ACTUAL): May 2, 2022
• Last Update Submitted That Met QC Criteria: April 24, 2022
• Last Verified: April 1, 2022

More Information

Terms related to this study

• Keywords: mobility; sarcopenia; sensor; acceptance; intelligent robotics; use-centric co-creation; elderly assistance; manipulability
• Additional Relevant MeSH Terms: Nervous System Diseases; Neurologic Manifestations; Neuromuscular Manifestations; Pathological Conditions, Anatomical; Muscular Atrophy; Atrophy; Sarcopenia
• Other Study ID Numbers: T42-717/20-R

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Data collected in this study will be published and submitted to academic journals to share with other researchers.
• IPD Sharing Time Frame: No limitations on the publications
• IPD Sharing Access Criteria: No limitations on the publications
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No