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Intro: The burden of post-COVID-related morbidity and mortality is significant yet undermined. We studied the morbidity and mortality outcomes of COVID-19 patients with moderate-to-severe diseases by 90-day post-hospitalization. Method(s): This retrospective cohort study included 510 COVID-19 patients admitted to Kepala Batas Hospital with moderate to severe diseases, requiring oxygen therapy during hospitalization (Malaysia COVID severity category >=5;WHO scale >=5), between January and August 2021. We conducted telephone surveillance for 90 days post-discharge from the hospital, assessing for post- COVID complications and mortality. Relevant clinical data were extracted from medical records. Multiple logistic regression was employed to examine factors associated with post-COVID mortality after index hospitalization. Finding(s): Among 510 patients, 51%(n=260) were male with a mean age of 52.1 (14.65) years. A third had hypertension (39.8%) and diabetes (31.4%). Only 15.5% were partially vaccinated and 4.9% had complete vaccination before hospitalization. Nearly 65% were supplemented with nasal prong or face mask oxygenation (<10L/ min), 25.7% received high flow oxygenation and 10% were mechanically ventilated. Approximately 23.3% (n=119) of patients were admitted to the intensive care unit. By 90-day post-hospitalization, 46% (n=203) reported residual symptoms: lethargy (14.5%), dyspnoea (12.2%), hair loss (7.5%), memory loss (6.3%), depression (3.9%), anxiety (2.7%) and 1.6% required home oxygen supplementation. Forty-four patients (8.5%) were re- hospitalized at least once, with 40.9% due to post-COVID complications. About 87% of patients attended their post-COVID clinic appointment. Nearly 13.5% (n=69) of patients died within 90 days after being discharged from the hospital. Adjusted for gender, comorbids and ventilatory status, age >=60 years (aOR 7.96;95%CI 3.75-16.92;p<0.001), diabetes (aOR 2.30;95%CI 1.12-4.72;p=0.024) and high oxygen requirement (aOR 3.41;95%CI 1.56-7.46;p=0.002), were associated with increased 90-day post-COVID mortality. Conclusion(s): Post-COVID morbidity and mortality are significant among survivors hospitalized for moderate- to-sever disease. Comprehensive care must be addressed to improve the outcomes of post-COVID patients.Copyright © 2023
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Intro: COVID-19 survivors suffer from variable limitations affecting their quality of life. We examined the functional and psychosocial outcomes among COVID-19 patients with moderate-to-severe diseases by three months post-hospitalization. Method(s): This retrospective cohort study included 510 COVID-19 patients admitted to Kepala Batas Hospital with moderate-to-severe diseases, requiring oxygen therapy during hospitalization (Malaysia COVID-19 severity category >=5;WHO scale >=5), between January and August 2021. We followed up with telephone surveillances by 90 days post-discharge from the hospital, assessing their performance in activities of daily living and psychosocial implications. Relevant clinical data were extracted from medical records. We compared patients with low (<10L/ min) versus higher (>=10L/min) oxygen requirements on the patient-reported outcome variables. Finding(s): Among 441 survivors (86.5%), half (n=223, 50.6%) were male, with a relatively young population with a mean age of 50.2 (13.73) years. Only 17.9% were partially vaccinated and 5.7% had complete vaccination before hospitalization. Nearly 70% were supplemented with nasal prong or face mask oxygenation (<10L/ min), 26.1% received high flow oxygenation and 4.1% were mechanically ventilated. By 90-day follow-up, >90% had their functionality returned to baseline before hospitalization. Only 1.6% required home oxygen supplementation. Compared with their baseline functionality, 4.8% were unable to perform basic household chores, 4.1% required assistance in mobilization and 2.5% became fully dependent on caretakers. Among 254 patients returning to work, 98% worked in the same institution but 18.9% required job scope adjustments. About 7.7% experienced post-covid stigma at home and/or work, 3,9% suffered from depression 5.7% became self-isolated and 0.9% had suicidal ideation or attempts. Functional and psychosocial outcomes were similar between patients with low and higher oxygen requirements (all p>0.05). Conclusion(s): Despite fair recovery outcomes reported by survivors with moderate-to-severe disease, a small proportion suffered from significant functional limitations and psychosocial adversity. Post-hospitalization care is essential to screen-detect post-COVID complications and provide timely interventions.Copyright © 2023
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A few patients who have recovered from COVID-19 develop persistent or new symptoms that last for weeks or months; this is called "long COVID" or "post-COVID-19 syndrome." Over time, awareness of the short- and long-term consequences of COVID-19 has increased. The pulmonary consequences are now fairly well established, but little is known about the extrapulmonary system of COVID-19, particularly its effects on bones. Current evidence and reports indicate a direct relationship between SARS-CoV-2 infection and bone health, with SARS-CoV-2 having a significant negative effect on bone health. In this review, we analyzed the impact of SARS-CoV-2 infection on bone health and assessed the impact of COVID-19 on the diagnosis and treatment of osteoporosis.
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COVID-19 , Osteoporosis , Humans , Post-Acute COVID-19 Syndrome , SARS-CoV-2 , Bone DensityABSTRACT
The aim of camouflaged object detection (COD) is to find objects that are hidden in their surrounding environment. Due to the factors like low illumination, occlusion, small size and high similarity to the background, COD is recognized to be a very challenging task. In this paper, we propose a general COD framework, termed as MSCAF-Net, focusing on learning multi-scale context-aware features. To achieve this target, we first adopt the improved Pyramid Vision Transformer (PVTv2) model as the backbone to extract global contextual information at multiple scales. An enhanced receptive field (ERF) module is then designed to refine the features at each scale. Further, a cross-scale feature fusion (CSFF) module is introduced to achieve sufficient interaction of multi-scale information, aiming to enrich the scale diversity of extracted features. In addition, inspired the mechanism of the human visual system, a dense interactive decoder (DID) module is devised to output a rough localization map, which is used to modulate the fused features obtained in the CSFF module for more accurate detection. The effectiveness of our MSCAF-Net is validated on four benchmark datasets. The results show that the proposed method significantly outperforms state-of-the-art (SOTA) COD models by a large margin. Besides, we also investigate the potential of our MSCAF-Net on some other vision tasks that are highly related to COD, such as polyp segmentation, COVID-19 lung infection segmentation, transparent object detection and defect detection. Experimental results demonstrate the high versatility of the proposed MSCAF-Net. The source code and results of our method are available at https://github.com/yuliu316316/MSCAF-COD. IEEE
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The COVID-19 outbreak and the Russia-Ukraine conflict are significant economic challenges for China. Meanwhile, the Regional Comprehensive Economic Partnership Agreement (RCEP) entered into force on 1 January 2022, establishing the world's largest free trade zone with the world's largest population, the most diverse mix of members, and the highest development potential for reviving China's economy. The RCEP's second chapter goes beyond current global and regional free trade agreements, stipulating tariff reductions and their methods, which have had a noticeable impact on member countries' imports and exports. This study investigates the impact of RCEP tariff concessions on China's imports and exports, as well as industry development, by examining the various types of tariff concessions and tax cuts available. © 2022, International Network of Customs Universities. All rights reserved.
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Purpose: This paper aims to identify the interaction of different intervention strategies implemented in Malaysia towards flattening the curve of COVID-19 cases. Since the outbreak of COVID-19, many approaches were adopted and implemented by the Malaysian government. Some strategies gained quick wins but with negative unintended consequences after execution, whereas other strategies were slow to take effect. Learning from the previous strategies is pivotal to avoid repeating mistakes. Design/methodology/approach: This paper presents the cause, effect of and connection among the implemented COVID-19 intervention strategies using systems thinking through the development of a causal loop diagram. It enables the visualisation of how each implemented strategy interacted with each other and collectively decreased or increased the spread of COVID-19. Findings: The results of this study suggested that it is not only essential to control the spread of COVID-19, but also to prevent the transmission of the virus. The Malaysian experience has demonstrated that both control and preventive strategies need to be in a state of equilibrium. Focusing only on one spectrum will throw off the balance, leaving COVID-19 infection to escalate rapidly. Originality/value: The developed feedback loops provided policy makers with the understanding of the merits, pitfalls and dynamics of prior implemented intervention strategies before devising other effective intervention strategies to defuse the spread of COVID-19 and prepare the nation for recovery. © 2023, Jack Kie Cheng, Fazeeda Mohamad, Puteri Fadzline M. Tamyez, Zetty Ain Kamaruzzaman, Maizura Mohd Zainudin and Faridah Zulkipli.
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The travel industry has been severely affected by the COVID-19 outbreak. The operating pressure on enterprises has sharply increased, leading to the prominent phenomenon of abusive supervision. Managers employ this management method so that employees perceive work pressure as motivation to work harder and improve their performance. Employees may adopt the behavior of defensive silence to protect themselves from abusive supervision, which can subsequently affect employee behavior. However, social capital and relationships may lessen this effect. This study analyzed survey data on 475 workers from the Chinese tourism service industry to examine the mediating role of workers' defensive silence under abusive supervision, employee behavior, and the moderating role of social capital. The results showed that abusive supervision does not promote employee performance but hinders employee growth. Employees' defensive silence also affects employee behavior and has a partially mediating role in the relationship between abusive supervision and employee behavior. Social capital can mitigate the negative impact of abusive supervision on employee behavior. This study theoretically expands the applicable scope of employee silence as a mediating variable and social capital as a moderating variable. It is helpful for managers to change their negative leadership style, follow the suggestions of employees, pay attention to the organizational atmosphere, and enhance their team cohesion. © 2023 by the authors.
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Targeted therapeutics for SARS-CoV-2 virus caused COVID-19 are in urgent need. Chansu has been reported to have broad-spectrum antiviral effects and widely used in Southeast Asian countries. This study aims to assess the efficacy of Chansu injection in treating patients with severe COVID-19. A randomized preliminary clinical trial was conducted and eligible patients were allocated to receive general treatment plus Chansu injection or only general treatment as control for 7 days. The primary outcomes of the oxygenation index PaO2/FiO2 and ROX, secondary outcomes of white blood cell count, respiratory support step-down time (RSST), safety indicators, etc were monitored. After 7 days of treatment, the oxygenation index was improved in 95.2% patients in the treatment group compared with 68.4% in the control group. The PaO2/FiO2 and ROX indices in the treatment group (mean, 226.27+/-67.35 and 14.01+/-3.99 respectively) were significantly higher than the control group (mean, 143.23+/-51.29 and 9.64+/-5.54 respectively). The RSST was 1 day shorter in the treatment group. Multivariate regression analysis suggested that Chansu injection contributed the most to the outcome of PaO2/FiO2. No obvious adverse effects were observed. The preliminary data showed that Chansu injection had apparent efficacy in improving the respiratory function of patients with severe COVID-19.Copyright © 2021 The Authors
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Immunotherapy plays an important role in cancer treatment by activating or suppressing the immune system. However, there are still a series of challenges to overcome regarding the delivery vehicles of immunotherapeutic agents and their effective activation at tumor sites. Meanwhile, owing to their well-hydrated environment and capability of immobilizing biological cargos, hydrogels in combination with immunotherapies provide a chance to enhance the antitumor immune response with reduced side effects. In addition, stimuli-responsiveness has been also widely applied to optimize the pharmacokinetics with an improved therapeutic outcome. In this review, we discuss the opportunities for the combination of immunotherapy and stimuli-responsive hydrogels, such as light, temperature, ultrasound and magnetically responsive hydrogels, for effective cancer treatment. Finally, we explore the potential of stimuli-responsive hydrogels as vaccine implants against cancer and Covid-19.
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Background Vedolizumab has proven efficiency in adults but data in paediatric inflammatory bowel disease (pIBD) is limited. We present the outcome of treatment with vedolizumab in refractory pIBD cohort. Study Design Retrospective and ongoing prospective review of all patients commenced on Vedolizumab following loss of response to anti-tumour necrosis factor [TNF] between Nov 2017 and Nov 2020. Aims and Objectives The primary outcome was remission at Week 14 and last follow up (wPCDAI/PUCAI<10) from commencing vedolizumab. The secondary outcomes were to review trend of biochemical makers, surgical interventions, and adverse effects. Results 11 children received vedolizumab (6[54%] males), mean age at time of diagnosis 12.45(8.34-15.48) with a median(IQR) time from diagnosis of 2.68(1.79-5.28)years;6 [54%] Crohn's disease [CD] and 5[46%] Ulcerative colitis/IBD Unclassified [UC/IBDU] (table 1). For CD;5/6 was treated previously with anti-TNF [40% primary failure, 60% secondary failure], all had colonic disease, 3/6 upper GI involvement and 3/6 perianal disease. One child with Bruton's agammaglobulinemia was anti-TNF naive when commenced on vedolizumab. All UC children were treated with anti-TNF [40% primary failure, 60% secondary failure], 80% had pan-colitis. Median age at time of commencing vedolizumab (V0) was 14.99(13.0-17.6). Baseline characteristics at V0;faecal calprotectin( FC) 2851(92-6000), Hb 114(96-146), ESR 22(4-90), albumin 39(27-46) and CRP 16.7(4-39.5). 4/11(36%) required surgery, three of whom had colectomy. 8/11 remained on immunomodulators with vedolizumab. Transient raised transaminases and eczema was reported once and low mood with suboptimal response noted once. 6/11(54%) were in remission 14 weeks from commencing vedolizumab (V14) and 4/11(36%) were excluded. At last follow up from commencing vedolizumab (VF), median years 2.21(0.78-3.43), 3 remained in remission. In CD cohort, one child had a defunctioning ileostomy and remained in steroid free remission (SFR) at V14 and VF (3.43 years) on vedolizumab monotherapy. One had colectomy (FC-3296 wPCDAI-60), steroid dependency compounded by methotrexate induced interstitial nephritis and vedolizumab was discontinued at VF (2.19 years). Two continue to have active disease at V14 after commencing vedolizumab. One had SFR at V14 and was transitioned at 2 years (FC-2585, wPCDAI-25) on vedolizumab. One with anti-TNF resistant disease, achieved clinical remission 9 months after starting vedolizumab (wPCDAI 2.5, FC 598) before being transitioned. In UC cohort, two had vedolizumab primary non-response needing subtotal colectomy. One patient with PUCAI 5 at V14 needed regime intensification for low vedolizumab levels but had active disease (PUCAI-25, FC-366) when transitioned at VF (2.06 years). One patient, who achieved remission whilst on steroid at V14, remains in SFR at VF (0.58 years) on concomitant immunomodulation and optimal vedolizumab level at end of induction (>19). One who was lost to follow-up during COVID, was transitioned on 4 weekly vedolizumab regime. Conclusion At V14, 54% of patients achieved clinical remission and we see significant improvement with PUCAI/PCDAI scores and faecal calprotectin in both UC and CD cohort. We are continuing this study over a longer period to achieve a larger cohort.
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Chest X-ray (CXR) is a common imaging modality for examination of pneumonia. However, some pneumonia signs which are visible in CT may not be clearly identifiable in CXR. It is challenging to create a good ground truth for positive pneumonia cases based on CXR images especially for cases with small pneumonia lesions. In this paper, we propose a novel CT-based CXR synthesis framework, called ct2cxr, to perform data augmentation for pneumonia classification. Generative Adversarial Networks (GANs) were exploited and a customized loss function was proposed for model training to preserve the target pathology and maintain high image fidelity. Our results show that CXR images generated through style mixing can enhance the performance of general pneumonia classification models. Testing the models on a Covid-19 dataset shows similar improvements over the baseline models. © 2022, Springer Nature Switzerland AG.
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Urbanization and Sustainable Development Goals (SDGs) are important global issues in the current “Anthropocene”. Climate change and the COVID-19 pandemic have exacerbated global urban problems and hindered the ability to meet SDGs on time, while the broad interlinkages between urbanization and the SDGs remain poorly understood. This study shows that among the interlinkages of urbanization with 17 SDGs, synergies are observed with 151 targets (89%), among which 67 (40%) have stronger synergies, and trade-offs are observed with 66 targets (39%), among which 31 (18%) have stronger trade-offs. Furthermore, the synergies and trade-offs between urbanization and the achievement of SDGs are specifically analyzed based on four fundamental interaction fields: (a) public health and social welfare equality;(b) energy consumption and economic growth;(c) natural resource use and ecological/environmental impacts;and (d) international cooperation for development. Finally, based on these analyses, we propose four recommendations for sustainable urbanization, including (a) shared well-being and spatial justice for urban and rural residents;(b) guiding green and low-carbon urban development;(c) building resilient cities;and (d) promoting multilateral cooperation in cities, which can contribute to the achievement of SDGs by 2030. © 2022
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With the rapid growth of the coronavirus disease of 2019 (COVID-19) cases, massive amounts of relevant data are being trained on machine learning models for countering communicable infectious diseases. Federated Learning (FL) is a paradigm of distributed machine learning to deal with the individual COVID-19 data, and enable the protection of data privacy. However, FL has low efficiency in Edge-Based wireless communication systems with system heterogeneity. In this paper, we propose an "Asynchronous-Adaptive FL" (AAFL) scheme. Specifically, we allow that medical devices with different performances have a heterogeneous number of local SGD iterations in each communication round, called asynchronous iteration strategy which is balanced under adaptive control. We theoretically analyze the convergence of the AAFL scheme under a given time budget and obtain a mathematical relationship between the heterogeneous number of local SGD iterations and the optimal model parameters. Based on the mathematical relationship, we design an algorithm for parameter server and work nodes to adaptively control the heterogeneous number of local SGD iterations. Subsequently, we build a prototype heterogeneous system and conduct experiments on various scenarios for analyzing the general properties of our algorithm, and then apply our algorithm to public COVID-19 databases. The experimental results and application performance demonstrate the effectiveness and efficiency of our AAFL scheme.
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Introduction: Gradual enlargement of multinodular goiter (MNG) may compress surrounding structures which may progressively cause complications of tracheal stenosis and airway compromise. Surgical resection remains the gold standard treatment in MNG patients presenting with respiratory distress. In the current global COVID -19 pandemic, compressive goiter should be a differential diagnosis in patients with stable benign thyroid goiter presenting with dyspnea. We present a case of MNG with life threatening airway obstruction during an active COVID-19 infection. Case presentation: A 74-year-old female with a history of hyperthyroidism with multi-nodular goiter and recurrent atrial fibrillation status-post ablation, was transferred to the intensive care unit for treatment after being intubated for respiratory distress at a nearby hospital. She was diagnosed with hyperthyroidism about 40 years ago and managed with methimazole. Over the last two years, thyroid ultrasound and prior imaging showed MNG with patent but moderate tracheal narrowing;fine-needle aspiration (FNA) confirmed benign colloid nodules with cystic degeneration. She was pending cardiac clearance for surgery when symptoms acutely worsened two days before admission. On initial assessment, she was hemodynamically stable, afebrile, with oxygen saturation of 86% on room air. She was alert and able to follow commands. On physical examination, she had stridor and thyromegaly was evident with mild tenderness on palpation. Cardiopulmonary examination was remarkable for coarse breath sounds. Labs showed TSH 4.82 (Normal 0.3 - 4.5 ulU/mL), FT4 0.64 (Normal 0.5- 1.26 ng/dL). Respiratory panel test came back positive for SARS-CoV-2. Racemic epinephrine and albuterol nebulizers were administered to help with her symptoms. CT scan of the neck revealed a severe narrowing and mild rightward shift of the trachea by a large multinodular goiter, prompting the decision to intubate for airway protection. CT scan of the chest with contrast demonstrated the large MNG with tracheal stenosis. Her methimazole dose was adjusted. After cardiac clearance, she underwent thyroidectomy through a transcervical approach. Levothyroxine and calcium supplementation were started post-surgery. She was extubated two days after her thyroidectomy. Pathology results showed no evidence of malignancy. Discussion: Acute airway obstruction by large MNG requiring emergent airway protection is rare. Typically airway compromise from large otherwise stable benign goiters results from sudden hemorrhage into a cyst, upper respiratory tract infection leading to tracheal edema, or worseningcomorbid conditions. During the COVID-19 pandemic, acute respiratory failure and shortness of breath is typical of worsening disease course. This case highlights the importance of maintaining wider differentials of respiratory failure even and we need to consider worsening of tracheal narrowing with a large goiter due to tracheal edema from SARS- CoV-2 Infection. Thyroidectomy before SARS-CoV-2 infection may have reduced her need for emergent intubation for acute respiratory failure by improving pre existing airway compression.Presentation: No date and time listed
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With increased human mobility and the introduction of NPIs, the complex, dynamic spread of COVID-19 has diverged significantly from SEIR's single, static assumption. At the same time, the ability to obtain front-line data also limits the modeling capabilities of SEIR. For researchers who cannot program, they must find suitable collaborators to implement their research. Even for researchers who can program, they need to repeat the principle and application process of the infectious disease model. LibEpidemic provide an open-source framework for modeling infectious disease, especially COVID-19, with bigdata. Researchers can implement subdivided, multi-stage or even metapopulation with the support of LibEpidemic. © 2022 ACM.
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Chest radiographs are widely used in the medical domain and at present, chest X-radiation particularly plays an important role in the diagnosis of medical conditions such as pneumonia and COVID-19 disease. The recent developments of deep learning techniques led to a promising performance in medical image classification and prediction tasks. With the availability of chest X-ray datasets and emerging trends in data engineering techniques, there is a growth in recent related publications. Recently, there have been only a few survey papers that addressed chest X-ray classification using deep learning techniques. However, they lack the analysis of the trends of recent studies. This systematic review paper explores and provides a comprehensive analysis of the related studies that have used deep learning techniques to analyze chest X-ray images. We present the state-of-the-art deep learning based pneumonia and COVID-19 detection solutions, trends in recent studies, publicly available datasets, guidance to follow a deep learning process, challenges and potential future research directions in this domain. The discoveries and the conclusions of the reviewed work have been organized in a way that researchers and developers working in the same domain can use this work to support them in taking decisions on their research. (c) 2022 Elsevier B.V. All rights reserved.
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During the regular COVID-19 prevention and control period, the running of fever-related clinical trial projects faces many problems, which will affect the development of new drugs. How to coordinate the regular COVID-19 prevention and control with the clinical trial process is the key to ensure that the clinical trial participants are successfully enrolled. In this paper, taking the influenza project as an example, combined with the practice of operation and management of the influenza clinical trial project in our hospital, the problems faced in the operation of fever-related clinical trial projects during the regular COVID-19 prevention and control period were discussed and the countermeasures and suggestions were proposed. In order to meet the dual needs of infectious disease prevention and control and clinical trials, it is recommended that in low-risk areas for COVID-19, the subject screening process be integrated with the COVID-19 exclusion process, the starting time of subject screening be moved forward, clinical trial enrollment be conducted while waiting for COVID-19 screening results, in addition, the clinical trial process after COVID-19 screening results are returned should be established in advance. Copyright © 2022, Chinese Journal of New Drugs Co. Ltd. All right reserved.
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Objective To understand the awareness, psychological status and stress reduction of health care workers involved in the emergency response Corona Virus Disease 2019 (COVID-19) outbreak since the “traffic control” in Dali Bai Autonomous Prefecture on 26 January 2020, in order to inform the development of relevant measures. To provide a reference basis for the development of related measures. Methods The study participants were invited through the Dali Bai Autonomous Prefecture medical and nursing exchange group by snowball sampling method based on WeChat from February 4 to February 5, and the invited participants filled out the questionnaires online(Questionnaire Star). The invailed questionnaires were strictly eliminated according to the quality control conditions, and the questionnaires that fit the research study were selected for collation, statistical analysis was performed. Results Onerall high awareness of COVID-19 among health care workers after “traffic control” in Dali Bai Autonomous Prefecture, with the highest knowledge of the source of infection was 95.95% and the lowest genotype knowledge rate of 64. 86%. The differences between the different psychological profiles of anxiety and stress, loneliness and depression among health care workers were statistically significant (x2 = 25. 439, P < 0. 01), and the highest percentage of anxiety among health care workers was 79. 73% and the lowest percentage of depression was 50. 85%;health care workers mainly reduced stress by watching TV and surfing the Internet, and the composition ratios of the two main forms of reducing stress were 68.92% and 60. 81%, respectively. Conclusion Different types of mental health problems existed among health care workers of different genders, occupations, titles and marital status after the “traffic control” in Dali Bai Autonomous Prefecture. Therefore, targeted mental health guidance and interventions for different health care workers. © 2022, Editorial Department of Medical Pest Control. All rights reserved.
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There is a growing trend for people to perform work-outs at home due to the global pandemic of COVID-19 and the stay-at-home policy of many countries. Since a self-designed fitness plan often lacks professional guidance to achieve ideal outcomes, it is important to have an in-home fitness monitoring system that can track the exercise process of users. Traditional camera-based fitness monitoring may raise serious privacy concerns, while sensor-based methods require users to wear dedicated devices. Recently, researchers propose to utilize RF signals to enable non-intrusive fitness monitoring, but these approaches all require huge training efforts from users to achieve a satisfactory performance, especially when the system is used by multiple users (e.g., family members). In this work, we design and implement a fitness monitoring system using a single COTS mm Wave device. The proposed system integrates workout recognition, user identification, multi-user monitoring, and training effort reduction modules and makes them work together in a single system. In particular, we develop a domain adaptation framework to reduce the amount of training data collected from different domains via mitigating impacts caused by domain characteristics embedded in mm Wave signals. We also develop a GAN-assisted method to achieve better user identification and workout recognition when only limited training data from the same domain is available. We propose a unique spatialtemporal heatmap feature to achieve personalized workout recognition and develop a clustering-based method for concurrent workout monitoring. Extensive experiments with 14 typical workouts involving 11 participants demonstrate that our system can achieve 97% average workout recognition accuracy and 91% user identification accuracy. © 2022 IEEE.