Background Understanding how prostheses are u sed in everyday life is central to the design, provision and evaluation of prosthetic devices and associated services . This paper reviews the scientific literature on methodologies and technologies that have been used to assess the daily use of both upper - and lower -limb prosthe ses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long -term monitoring. Methods A systematic literature search was conducted in PubMed , Web of Science, Scopus, CINAHL and EMBASE of studies that monitored the activity of prosthesis -users during daily -living. Results 60 lower -limb studies and 9 upper -limb studies were identified for inclusion in the review . The first studies in the lower -limb field date from the 1990s and the number has increas ed steadily since the early 2000s . In contrast, the studies in the upper -limb field have only begun to emerge over the past few years. The early lower -limb studies focused on the development or validat ion of actimeters , algorithms and/or scores for activity classification . However, most of the recent lower -limb studies used activity monitoring to compare prosthetic This is a p re-print of the paper ‘Technology for monitoring everyday prosthesis use: a systematic review ’, by Chadwell, Diment, Mico Amigo, Morgado Ramirez et al. 2 components . The lower -limb studies mainly used step -counts as their only measure of activity, focusing on the amount of activity, not the type and quality of movements. In comparison, t he small number of upper -limb studies were fairly evenly spread between development of a lgorithms, comparison of everyday activity to clinical scores, and compari son of different prosthesis user populations. Most upper -limb papers reported the degree of symmetry in activity levels between the arm with the prosthesis and the intact arm . Conclusions Activity monitoring technology used in conjunction with clinical scores and user feedback, offer s significant insights into how prostheses are used and whether they meet the user’s requirements. However, the cost, limited battery -life and lack of availability in many countries mean that usin g sensors to understand the daily use of prostheses and the types of activity being performed has not yet become a feasible standard clinical practice. This review provides recommendations for the research and clinical communities to advance this area for the benefit of prosthe sis users. Keywords actimetry; activity monitoring; amputation; gait; prosthetic; Introduction The World Health Organization (WHO) provides a global estimate of 35–40 million people who require prosthetics and orthotics services ,1 and this demand is increasing due to a range of factors . The growing and aging global population , along with the rising incidence of vascular -related diseases has led to high amputation rates.1–4 Urbanisation contributes to an increasing number of traffic accidents, and conflict and war , particularly in the Middle East and East Africa , have caused high r ates of traumatic injur y leading to amputations .5 Appropriate prostheses and supporting services can result in improve d mobility, function, aesthetics and comfort for the user.6 Consequently , prosthesis provision can improve the ability of a person with limb absence to generate an income an d participat e in education and social activities, increasing their quality of life .7 Prosthesis use may also reduce the severity of some comorbidities, and the medical and support costs associated with them .8 The WHO recommend s that p rosthetic service provision should take an integrated approach, which should include fitting the prosthesis, training the wearer, rehabilitation, community suppo rt and repair services .9 However, the WHO also identified that access to prosthetic and orthotic services is a particular challenge, including a lack of service provision, problems with service delivery associated with inadequate staffing or This is a p re-print of the paper ‘Technology for monitoring everyday prosthesis use: a systematic review ’, by Chadwell, Diment, Mico Amigo, Morgado Ramirez et al. 3 trainin g, lack of funding, and crucially a lack of data and evidence.10 Indeed , evidence on the best ways to design and distribute prostheses to make them widely accessible, affordable and meet the users’ needs is lacking.11 Prosthetic service and design decisions are predicated on the assumption that the prosthetic devices are worn and used in users’ everyday lives .12 13,14 When user centred design principles are used, prosthetic devices are better match ed to the user’s needs , leading to better functional outcomes .15 However, there is currently limit ed objective data on how much and when prostheses are worn, what tasks they are used for, and what individual adjustments to the design of prosthes es would increase their usefulness for the wearer in their environment . To capture data on everyday use of prosthes es, several clinical questionnaires and self -reported surveys have been proposed.16,17 Such tools typically ask the respondent to estimate prosthesis use (e.g. hours of wear per day) and/or the set of everyday activities performed (e.g. walking/sitting/community participation ).16,17 Questionnaires that rely on self -reported measures are time -consuming for clinicians to administer and fo r users to complete. They provide only summary data , and lack accuracy because they are limite d by the users’ comprehension and interp retation of the questions, their social bias and their recall.13 Further, in countries where access to secondary or higher education is limited, users’ literacy and numeracy levels can be a barr ier to the efficacy of questionnaires. In order to evaluate how well a prosthesis is meeting users’ needs , it is essential that users ’ voices are included in the assessment and that qualitative research methods are used . However, d igital technologies that can objectively monitor the use of prostheses offer a complementary approach to these other assessment methods for understanding the effectiveness of different prosthetic designs, componentry, and rehabilitation and lifestyle interventions .18–21 There is a large body of literature on activity monitoring, but little has looked at measuring the activity of people who use prosthe ses.22–24 Previous reviews of studies that monitor the physical activity of people with limb absence have focused on the lower -limb and on the applic ation of activity monitoring techniques , using sensors to compare prosthetic componentry,18 and assessing the physical and mental health benefits of physical activity.25 This paper is intended to have general relevance to people who use prosthetic dev ices, but was motivated in particular by collaborative research towards addressing the global challenges around prosthetics services in low- resource settings and lower - and middle -income countries (hereafter grouped as low-resource settings ). The review discusses the challenges around t he assessment of prosthetic device use in low-resource communities . Whilst advanced movement analysis methods such as motion capture offer detailed insights into gait quality, such facilities are rarely available in low-resou rce settings and service providers report a greater need to assess more general pat terns of longer -term prosthesis use.26,27 People may receive training to use their prosthesis in a This is a p re-print of the paper ‘Technology for monitoring everyday prosthesis use: a systematic review ’, by Chadwell, Diment, Mico Amigo, Morgado Ramirez et al. 4 clinic, but their continuing use after returning home i s completely unknown, as is the potential change in physical behaviour which their prosthetic or orthotic device may enable. Therefore, t his paper reviews the scientific literature on methodologies and technologies that have been used to assess the commun ity-based, daily use of both upper - and lower -limb prosthe ses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long -term monitoring . Methodology Search strategy This systematic literature review employed a search of publications up to November 2019. Five databases (PubMed , Web of Science, Scopus, CINAHL and EMBASE) were used to search for relevant articles using three groups of keywor ds to collect all studies that monitored the activity of prosthesis -users during daily -living . Community -based activity: "daily living" OR "free living" OR "daily life" OR "real world" OR activit* OR mobility OR "prosthetic use" OR "home use " OR "real life " OR "daily use" AND Population of interest: "artificial limb" OR "artificial leg" OR "artificial arm" OR (prosthe* OR amput* AND (limb OR leg OR arm OR hand OR wrist OR elbow OR foot OR ankle OR knee OR transradial OR trans -radial OR transhumeral OR trans -humeral OR transtibial OR trans -tibial OR transfemoral OR trans -femoral)) AND Sensor for monitoring activity : actimetry OR sensor OR monitor* OR "inertial measurement unit" OR IMU OR acceleromet* OR gyroscope OR magnetometer OR "global positioning system" OR GPS OR "step count" OR pedometer OR "cadence" OR "steps/" OR "steps per" Study selection After removing d uplicates , the title and abstract of each publication were reviewed to determine its relevance . Any paper that did not report first -hand on digital ly monitoring the activities of prosthesis -users in a community setting (i.e. outside the lab or clinic) were excluded. Conference abstracts that did not link to a full conference paper were also excluded. Where the relevance was not clear from the title a nd abstract , papers were read in full to determine inclusion. For each included paper , the reference lists and forward citation reports from each This is a p re-print of the paper ‘Technology for monitoring everyday prosthesis use: a systematic review ’, by Chadwell, Diment, Mico Amigo, Morgado Ramirez et al. 5 database were consulted in order to identify additional relevant articles that were not found in the automatic search . Analysis of studies The papers were categorised by study type (words in italics are used as category abbreviations) :  Studies that d eveloped or validated activity monitoring devices, algorithms and/or metrics for activity description, intensity an d/or classification .  Studies that c ompar ed metrics reflecting activity levels to clinical scores .  Studies that c ompared interventions (including prosthetic components and lifestyle interventions).  Studies that compared predefined populations . Information w as collected from each included paper on the aim and main findings, the population, sample size, types of sensors, locations of sensors, duration of the assessment, types of activity detected and amount of prosthesis use. The analysis divides the level of limb absence into 4 types; below knee, including Syme’s and partial -foot (BK), above knee, including knee and hip disarticulation (AK), below elbow, including w rist disarticulation and partial -hand (BE), and above elbow, including elbow and shoulder disart iculation and forequarter (AE). For 25% of the included studies, a double -blinded triangulation method was used to complete the analysis. The papers were divided up between 9 of the authors so that the classification of the papers into type of study and information collected from each paper could be compared between reviewers, reducing the risk of bias. There were few disagreements, and these all occurred in determining the primary category for papers that fitted into multiple categories. Therefore, LD and AD reassessed lower -limb papers that fitted into multiple categories and AC and LK reassessed the categories of the upper -limb papers to ensure a consensus was reached for all studies . Results The search found 2793 papers across the 5 databases ( Figure 1). After removing duplicates, 1716 papers were screened by title and abstract. Of these, 57 lower -limb studies and 5 upper -limb studies were identified as relevant. An additional 3 lower -limb studies and 4 upper -limb studies were fou nd through analysis of the